A CRM system is an essential tool for businesses to manage customer interactions effectively. There are numerous CRM software options available in the market.
In this article, we’ll delve into five reasons why it’s wise to invest in building a custom CRM. Firstly, custom CRMs are tailored to meet specific business needs and workflows, leading to more efficient processes and increased productivity. Secondly, custom CRMs offer enhanced security measures and better data privacy protection. Thirdly, a custom CRM can integrate seamlessly with your existing systems, providing a unified view of customer data.
Finally, building a custom CRM can be more cost-effective in the long run, as businesses can avoid ongoing licensing fees and expensive customization costs associated with off-the-shelf software.
Unique Functionalities
One of the primary benefits of creating a custom CRM system is the ability to add unique functionalities that are customized for your business. Pre-built CRM software may not provide the flexibility required to tailor your customer interactions and user experience. With a custom CRM, you can add personalized dashboards, customized reports, and workflows that match your business processes.
This can significantly improve productivity and efficiency, as well as provide a competitive advantage over businesses that use generic CRM solutions.
Integration with Another System
Building a customized CRM system provides an opportunity to integrate it seamlessly with other essential business systems. Pre-packaged CRM solutions may not offer the required level of integration, which can lead to disconnected data silos and inefficient processes. A bespoke CRM solution can be designed to work in tandem with other critical systems, such as ERP, accounting, and marketing automation software.
This creates a unified view of customer data, streamlines operations, and eliminates manual data entry errors. Customized integrations also help automate repetitive tasks, freeing up valuable employee time.
Security Data
One of the most significant advantages of creating a custom CRM system is the ability to implement robust security measures to protect customer data. Pre-built CRM software can have vulnerabilities that leave customer data at risk of external threats, which can compromise customer trust.
A custom-built CRM system allows businesses to design security protocols and data privacy policies that align with their specific needs. This includes implementing encryption, access control, and data backup and recovery measures.
Eases Scaling Process
Creating a custom CRM solution can help businesses ease the scaling process as they grow. As a company expands, its customer management requirements become more intricate, and out-of-the-box CRM software may not be adequate to handle the increased workload.
With a customized CRM solution businesses can tailor their CRM system to meet their evolving needs, adding features, functionalities, and integrations as required without switching to a new CRM platform entirely.
What is CRM Application Development?
CRM application development is the process of building a customized customer relationship management system for businesses. Such systems are designed to help businesses manage their customer interactions, optimize their sales and marketing processes, and improve customer retention rates. Although there are off-the-shelf CRM solutions available, a custom CRM application provides businesses with a bespoke solution that caters to their unique needs.
The development process for a custom CRM application typically involves several stages. Firstly, a comprehensive analysis is conducted to understand the specific challenges and opportunities that the CRM system needs to address. This includes an evaluation of the current processes, data structures, and integrations that are in place.
Next, the development team creates a customized solution that addresses the identified challenges and opportunities. This may involve the creation of new features, the integration of existing software and systems, and the implementation of tailored security and privacy measures.
The coding and testing phases follow the design phase, with the development team creating the software and testing it thoroughly to ensure that it meets the business’s requirements and functions correctly.
Conclusion
Creating a customized CRM solution provides businesses with a wide range of benefits that cannot be found in off-the-shelf CRM software. A tailored CRM application offers unique features and functionalities that address a business’s specific needs, enhancing the effectiveness and efficiency of its sales and marketing processes.
Moreover, Custom CRM Applications can be seamlessly integrated with existing software and systems, streamlining operations and saving time and resources. Additionally, custom CRM systems offer advanced security features that protect customer data, reducing the risk of data breaches and ensuring compliance with data protection regulations.
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AI bots hungry for data are taking down FOSS sites by accident, but humans are fighting back.
Software developer Xe Iaso reached a breaking point earlier this year when aggressive AI crawler traffic from Amazon overwhelmed their Git repository service, repeatedly causing instability and downtime. Despite configuring standard defensive measures—adjusting robots.txt, blocking known crawler user-agents, and filtering suspicious traffic—Iaso found that AI crawlers continued evading all attempts to stop them, spoofing user-agents and cycling through residential IP addresses as proxies.
Desperate for a solution, Iaso eventually resorted to moving their server behind a VPN and creating "Anubis," a custom-built proof-of-work challenge system that forces web browsers to solve computational puzzles before accessing the site. "It's futile to block AI crawler bots because they lie, change their user agent, use residential IP addresses as proxies, and more," Iaso wrote in a blog post titled "a desperate cry for help." "I don't want to have to close off my Gitea server to the public, but I will if I have to."
Iaso's story highlights a broader crisis rapidly spreading across the open source community, as what appear to be aggressive AI crawlers increasingly overload community-maintained infrastructure, causing what amounts to persistent distributed denial-of-service (DDoS) attacks on vital public resources. According to a comprehensive recent report from LibreNews, some open source projects now see as much as 97 percent of their traffic originating from AI companies' bots, dramatically increasing bandwidth costs, service instability, and burdening already stretched-thin maintainers.
Kevin Fenzi, a member of the Fedora Pagure project's sysadmin team, reported on his blog that the project had to block all traffic from Brazil after repeated attempts to mitigate bot traffic failed. GNOME GitLab implemented Iaso's "Anubis" system, requiring browsers to solve computational puzzles before accessing content. GNOME sysadmin Bart Piotrowski shared on Mastodon that only about 3.2 percent of requests (2,690 out of 84,056) passed their challenge system, suggesting the vast majority of traffic was automated. KDE's GitLab infrastructure was temporarily knocked offline by crawler traffic originating from Alibaba IP ranges, according to LibreNews, citing a KDE Development chat. [...]
Tarpits and labyrinths: The growing resistance
In response to these attacks, new defensive tools have emerged to protect websites from unwanted AI crawlers. As Ars reported in January, an anonymous creator identified only as "Aaron" designed a tool called "Nepenthes" to trap crawlers in endless mazes of fake content. Aaron explicitly describes it as "aggressive malware" intended to waste AI companies' resources and potentially poison their training data.
"Any time one of these crawlers pulls from my tarpit, it's resources they've consumed and will have to pay hard cash for," Aaron explained to Ars. "It effectively raises their costs. And seeing how none of them have turned a profit yet, that's a big problem for them."
On Friday, Cloudflare announced "AI Labyrinth," a similar but more commercially polished approach. Unlike Nepenthes, which is designed as an offensive weapon against AI companies, Cloudflare positions its tool as a legitimate security feature to protect website owners from unauthorized scraping, as we reported at the time.
"When we detect unauthorized crawling, rather than blocking the request, we will link to a series of AI-generated pages that are convincing enough to entice a crawler to traverse them," Cloudflare explained in its announcement. The company reported that AI crawlers generate over 50 billion requests to their network daily, accounting for nearly 1 percent of all web traffic they process.
The community is also developing collaborative tools to help protect against these crawlers. The "ai.robots.txt" project offers an open list of web crawlers associated with AI companies and provides premade robots.txt files that implement the Robots Exclusion Protocol, as well as .htaccess files that return error pages when detecting AI crawler requests.
You may have seen some headlines floating around of Netflix using "AI on 300 titles in the last year
It took me a moment to find an article that actually links to the source of information
article: https://www.cnet.com/tech/services-and-software/netflix-300-programs-this-year-ai-production-q2-earnings/
the pdf they link: https://s22.q4cdn.com/959853165/files/doc_financials/2026/q2/Netflix-Inc-_Earnings-Call_2026-07-16T00_00_00_English-1.pdf
i got sick of articles not mentioning what the shows were shows (or elaborating that the source didn't provide that information at least)
and i got sick of articles not actually investigating the ways in which Netflix implements the specific AI it uses
and i got sick of articles also bringing up the unconnected "AI Actress" that seems more like a media stunt since it's "work" seems to total to 2 youtube videos
so i'm going to do another public statement from a media company breakdown (like i did here) where I will wear my scepticism and bias against gen AI openly (please remember that it’s not the concept of machine learning/neural networks I take issue with it’s the ethical issues of how they are currently developed and implemented.) but the misapplication of the term AI makes it hard to actually understand what is being talked about when we talk about AI and I wanna demystify it somewhat to the best of my understanding. I also wanna rant a bit about where my interpretation of these topics is at currently
The first instance of the relevant to the headlines topic occurs on page 11 of the PDF, everything before that is mostly standard money talk and discussions of content expansion (“video games and more recently, vertical video clips and podcasts”)
"Spencer Wang, Vice President of Finance, Corporate Development & Investor Relations: Our next question comes from Sean Diffley of Morgan Stanley [Global financial firm]. What have been the early learnings from the InterPositive deal?"
Note: InterPositive being the AI film production company founded by Ben Affleck in 2022 To take a detour to that announcement for context on how that tech might be applied, here’s Ben Affleck’s statement (edits mine to omit flourishes of language)
Netflix announced the acquisition of InterPositive, the filmmaking technology company founded by Ben Affleck that develops AI-powered tools
"Together with a small team of engineers, researchers and creatives, I began filming a proprietary dataset on a controlled soundstage with all the familiarities of a full production
[...]
our first model, trained to understand visual logic and editorial consistency, while preserving cinematic rules under real-world production challenges such as missing shots, background replacements or incorrect lighting. We also built in restraints to protect creative intent, so the tools are designed for responsible exploration while keeping creative decisions in the hands of artists — and ensuring that the benefits of this technology flow directly back to the story they're trying to tell.
The results of this foundational work were deliberately smaller datasets and models focused on filmmaking techniques — rather than performances — creating tools that artists can use, control and benefit from.”
Emphasised in this statement are:
the small scale of the production (what may be the Linkedin lists the size as 11-50 employees with only one user account listed on the page.)
The custom Data Set created in-house
The use of smaller datasets and models
That last point is a more ethical element that is possible but something that runs counter to how widespread machine learning generally seems to operate when trying for accuracy to life, they don’t elaborate on how this issue of scale is handled.
Not included is if any of these models are trained on external sets at any point for supplemental data, or where the machines required for processing are operated from, presumably in house but there’s no guarantee. Also not mentioned is if using this tech means the data it collects is private and proprietary, or whether it will be used in the future.
In this Netflix interview/promotion the conversational explanation of how this works is as follows: [again, edits mine to omit hype]
“It's not about text prompting or generating something from nothing. You’re building a model from your own material. That's how this works. You have to create your movie essentially first before you can really build your model around your movie using AI. And once you do that, you have your model.
[…]
You use this technology to learn from your own film dailies. Then you're able to introduce that in the post-production process so that you're improving your editorial process, your ability to mix, color, finish your film, do visual effects. [...] It can only understand this and only build this tool because it's trained on the character that the actor has already built.
[…]
I want to take out all the logistical, difficult technical stuff that often gets in the way. You can use your own model to remove the wires on stunts, reframe a shot, get a shot you missed, shape the lighting, enhance the backgrounds. If you can take some of those problems out, yes, you can do it more quickly, you can do it more easily, […]”
So again, Not much specifics on what the actual processes are beyond a post production focus. The implication is video generation and effects modelling.
To theorise a bit- (from my limited outsider understanding)
“Film dailies” providing visual details that their tech would presumably be using as a template and altering using physics and realism learnt through the in-house training process.
Reframing and coverage of missed shots would probably involve a generative video situation.
Shaping the lighting and enhancing the backgrounds also but perhaps in a manner closer to a smart filter or the “upscaling” of making up what pixels make the image look sharpened.
My question is: something like removing a wire, how much of that is essentially automating the established colour keying/digital painting/cgi generation tools using logic based on machine learning, and how much is frame by frame image generation where you essentially have the original frame as the input and the output is a photorealistic image of pixels based on the machine learning (what’s the difference? Layers of separation/abstraction from the pixels representing the original image sensor data captured from reality). There are plenty of tools that use neural networking for machine learning to automate results that aren’t “generators”, such as auto selection for motion tracking or adjusting effects automatically based on information in the frame instead of manually adjusting values and processes in software. It’s unclear if these are what they are talking about.
So Ben Affleck’s spin is: This is small scale, curated, specific, and replaces tedious elements of production and post production. The implication is that this supports crew and performers and cuts down on hours and labour.
What Ben Affleck does NOT say: What it specifically does when applied in a task, how it might do it, what is done with the information collected once that project is completed, where the processing takes place.
Let’s climb back out of this digression back to the Netflix PDF. We now know that InterPositive is an effects and production company, founded by a celebrity, using vaguely defined machine learning to train small scale datasets custom to each project.
“What have been the early [since the 6th of March 2026] learnings from the InterPositive deal? And how should we think about potential cost savings in content creation? […] could this impact your $20 billion cash content budget on a go-forward basis? Or is it more likely to be reinvested into more content and better compensating talent?”
So the question is ‘it’s been 4 months since you got this technology, is it worth it or would it be better to pay more people to do the same thing for real?"
“Theodore A. Sarandos, Co-CEO, President & Director:
[…] it's early days for InterPositive, but we're broadly seeing that gen AI is starting to have an impact across hundreds of our productions. So important to note that we have other gen AI tools in addition to InterPositive. We're thrilled with all the speed they're bringing to market for us. But we also have Eyeline [ Formerly Scanline VFX, a Canadian visual effects and animation company founded in 1989 ] and we have our animation lab. […]”
This initial statement calls InterPositive contributions generative AI by grouping it with gen AI tools Netflix already used previous to this year.
Then he groups the company in with their animation and visual effects departments.
“gen AI is scaling quickly across the entire creative process, from concept to pre-vis through post and delivery. We're making higher quality output more quickly and efficiently than we could have using traditional methods. So gen AI workflows now have been used in roughly 300 of our titles with the largest concentration right to date is on post-production. But we're leveraging gen AI for really complicated shots and sequences. […] things like enhancing crowds or historical battle scenes, those kind of things.”
THIS section, one sentence of this section, is what entire articles are spun out on.
He starts with highlighting general applications: “concept to pre-vis through post and delivery.” Just stating they use it and it’s faster is not enough hype so the phrase “higher quality” is then applied (debatable) and “efficiently” is also used, however the application of that term to gen AI is one I have quibbled over before and still maintain actually means just paying less people for something to happen faster.
“gen AI workflows now have been used in roughly 300 of our titles with the largest concentration right to date is on post-production.” THE Headline sentence,
What it means by “workflows” is vague but post-production being singled out is at least something. “roughly 300” is frustratingly vague and again it’s not clear if they are talking about something as innocuous as sound isolation or automating motion tracking, to something subtle like artificial lighting, to something more like cgi in effect or even the type of promotional images that would be achieved through a quick collage with airbrushing/editing the appearance of the source image or generating promotional ad copy text.
“complicated shots and sequences” does that me pre-visualisation before filming? Does that mean taking the dailies and trialling different framing angles or shot sequences? does that mean using it to paint over the behind the scenes and generate a virtual set/effects?
(Side note: it is within possibility to take standard machine learning and apply it to mechanical camerawork through standard use data for essentially a more versatile steadicam/drone/rig control to automate complex camera motions. If you want an example of a non generative application of this sort of tech for “complicated shots and sequences” (there’s already normal computer powered pre-programing and tracking) )
“enhancing crowds or historical battle scenes” so what Wētā Workshop did in 2001 but I supposedly though less rendering/hardware requirements. I am unclear on how much less because what is the difference between a render farm and a data centre other than the manner in which information is processed because if anything render farms seem much smaller scale for the ‘same’ output. And again normal CGI already automates a lot of this sort of thing through both asset libraries and regular programming.
Four paragraphs might seem excessive for me to break down one paragraph but considering that paragraph still tells us so little but kickstarted the whole news flurry I felt like it was necessary.
“keep in mind that in many of the cases, productions would have left out those key shots because they just wouldn't have been able to afford them, they wouldn't have been able to do them in the time frames that they're working on.”
YOU SET THE BUDGET AND YOU SET THE TIMES! Get better at your job or accept things take time
“So those sequences are saved by the availability and access to these Gen AI tools.”
They could also have been saved by better scheduling and funding. And there are PLENTY of successful film and tv productions made on lower budgets and shorter production schedules. Sorry to be like Get Good but apparently Stranger Things series 5 cost up to $400-480 million, took 2 years of pre-production, took 1 year to film, and 10 months post production, before airing with a month intermission splitting a single season. And it wasn’t even good. So forgive me if I find the budget and time frame argument a bit dubious from this company.
“On the content side, we believe it takes great artists to make something great, and AI is not changing that. AI will give creators better tools to bring their visions to life. Movies are being made by people who make movies. AI provides them with better tools to make them even better.”
Again that sticky use of the word “better”, like “efficient” I am extremely sceptical of it. The use of “tools” is also questionable depending on what job the artists actually want to be doing since most artists like actually doing things themselves.
“Movies are being made by people who make movies” is asinine, of course, but also if I can get deep with it: Advertisements are also made by people who make movies. Movies are sometimes made by people who are only there for the pay-check on the way to the movie they want to be making. Movies are sometimes made by people contractually obliged to step in and finish the thing. Sandwiches are being made by people who make movies. Let’s be for real here. Sometimes people who make movies are using AI because their parent company told them to and not because they actually need it. This false sequentiality of technology will never not be annoying. The type of person who thinks 3D animation is better than or the successor to 2D, or that a photograph of a flower is better than a painting, when they are simply two different mediums with different aesthetic priorities. The same sort of mindset is being pushed by every person who claims the final result of generative AI is better than something created using regular computing or physical work. Just highlights that either they don’t know what the technology actually is or does or they want people who don’t know what the technology is or does to believe them and buy into the hype.
Not to mention the constant gen AI propaganda of ‘it’s just a tool’ and ‘this won’t replace artists it will help them’ which is so widespread. Is it ‘just’ a ‘tool’ or is it a huge innovation? People argue it’s both when it might be less than either- a different method of processing existing tools using massive resources.
Back to the talk:
“our talent leverages tools for things like set references and pre-vis and VFX and sequence prep and shot planning, which all makes the production itself so much more smooth and efficient and fast.”
Ah! Specificity at last (kinda) ! so it IS for rendering imagery beforehand (an entire job), running through what a shot might look like or could have added in post (a normal part of the iterative process and probably something you want your creative team actively thinking about rather than offloading for consistency if nothing else), and shot planning (again vague how much of this is ‘streamlining’ a process versus replacing the work entirely) “So much more smooth and efficient and fast”. Smooth depends on what is actually being done which isn’t really described. Efficient again is debatable and might just mean paying less people. Fast, I will grant you, that is the big appeal.
“ We're seeing it across the entire production life cycle and AI -- those use cases are scaling faster and faster.”
Yes sure the way this sort of technology develops is acceleratory and when it does hit a plateau resources are expanded. Is the cost of resources worth it? (see various ethical concerns) Is achieving something indistinguishable from regular human labour worth it? (what is THE POINT if it isn’t visually distinct)
“our documentary series we just released […] That series features 17 minutes of AI-enhanced footage. It enabled us to expand the scope of the series in ways that just wouldn't have been feasible before. Those 17 minutes, Sean, they were produced twice as fast and at half the cost of previous options.”
I’m not interested in hunting down AI in Netflix properties (they’ve caught flack for ai in the opening credits of a marvel show before so it is obvious sometimes) but we FINALLY got given a name of a SINGLE title of 300 supposed use cases. 17 minutes does not mean much as still images can be on screen for a while, but the fact that a documentary is presenting things that have been essentially altered without being too obvious or open about it- in the way you might a re-enactment for true crime- is concerning, just definitionally.
Anyway here’s an example of one of the enhancements I got from clicking to a random spot: they took a WOOD ENGRAVING and “enhanced” it by trying to make it look like a paper illustration in a method that removed the vertical etchings and left behind muddy writing and cropped out the name of the artist. Howard Pyle from Harper's Magazine, March 1882, btw. I checked and neither on screen nor in the sources in the credits was this information found.
“by equipping creators with these tools, we believe they're going to enhance their abilities, and we are going to have better and more impact for every dollar we spend on our programming. So content creation time lines can be shortened and quality can be enhanced.
So the cost savings will likely be reinvested into more content on the service, which fuels high-quality engagement and that whole kind of revenue profit flywheel that's going to come from that, that we've been talking about from day 1.”
Sick of hearing the term “enhanced” which could mean anything at this point. “better and more impact” another moment of strange vague hype phrasing. “time lines can be shortened” I still think probably the main draw being pushed here. “cost savings will likely be reinvested into more content on the service,” tricky thinking here- cost savings is how you promise money for investors, more content is how you promise to create that money, but is this not circular reasoning? Has the profits helped any of the 11 shows cancelled after only one season so far only halfway into this year? How much “high-quality engagement” can you make if your model trajectory seems to be cheaper and faster but also more money but it’s spread out to more shows?
SO WHAT DO WE KNOW?:
Netflix have multiple AI services they use for multiple stages of production
They bought a small scale AI company from an A list celebrity and broadly advertised this acquisition of a company that had no prior attention over the first 2 years of existence until it’s sale. This created press for the actor, Netflix, and added to attempts to legitimise the use of AI in media production without actually giving concrete examples.
When asked about if this acquisition was worth it they said they use it alongside other AI services and regular production
They then went on to advocate their use of AI due to how it is faster and also only a tool and also makes results better and also makes things run smoother and cheaper and also doesn’t take control away from artists.
They also listed a bunch of jobs and tasks that are already accomplished by people and computers without machine learning.
Of 300 supposed use cases they listed a single miniseries of which 17 minutes out of 369 minutes was “enhanced” by AI (could mean anything but I confirmed at least one case of “hand drawn filter” on a wood carving)
Generative AI is apparently used across the entire pre-production, production, post production, marketing process.
It is not clear what is actually being done
No directors or crew actors who don’t own AI companies gave their opinion on working with this tech in the 3 articles I read or the earnings meeting.
“that we've been talking about from day 1.”
Okay, well I got a lot of rambling from this one short response turned headlines, so just for fun let’s look at day one: let’s do a little comparison between the Q2 release for 2007 versus 2026 (financial results and earnings call)
Reed Hastings, Netflix co-founder and chief executive officer:
“Online DVD rental is a large and attractive opportunity and we remain committed to investing in our long-term growth. With yesterday’s price cuts in two of our most popular subscription plans, together with the reductions in February and June, we are choosing to lower price and reduce marketing as the most efficient means of sub growth and retention in the current competitive environment, and we are lowering our full-year guidance for revenue, subscribers, and earnings accordingly.”
Cute.
Full transcript of the Netflix, Inc. (NFLX) Q2 FY2007 earnings call held on July 23, 2007. Read the prepared remarks and analyst Q&A.
“As we look at how to grow our business most efficiently, we make trade-offs between service levels, marketing levels and price levels.”
“At lower prices, we will spend less acquiring subscribers than we otherwise would have because of the increased attractiveness of our lower-priced programs. In other words, marketing reductions largely fund these price cuts.”
“The tactics of our increased growth investments are higher service levels, lower pricing and slightly less marketing because we believe that is the most efficient combination for Netflix at this point.”
I see a theme here.
Also something before their shift from hosting to producing media:
“Adding titles doesn’t particularly cost us. It’s the actual viewing, so the more people watch, the more we owe the studios, which is fair and appropriate.”
And more ominously-
“The next big step -- delivering Netflix online video to the television -- we expect to come together next year with a number of partners and we’ll have more to say about that next year. One subscription service with two delivery methods is we believe the path to long-term leadership and profits.”
“I’d say our competitive view is that we should focus forward in online video, so if you see us doing various partnerships, we would be probably more inclined to do that. In the area of which -- we’re an Internet company, we look forward on these things, rather than trying to go tit-for-tat with Blockbuster on more their core area being store logistics.
Today, stores are probably more relevant to most consumers than online video, partially because it’s only to the laptop. But stores are going to be less relevant every year over the next five years and online video is going to be more relevant every year over the next five years.
We have a great balance sheet. We’re investing in online video.
We’re moving forward and that’s the way we look at the world.”
New Delhi [India], May 4: In a significant development in India’s fast-evolving technology services sector, SB Infowaves, under the leadersh
Shreya Parasrampuria Leading SB Infowaves Toward the Future of Scalable Artificial Intelligence
In this era of fast-changing technologies, companies are always on the lookout for revolutionary technology solutions that would allow them to stay ahead in the game. Spearheaded by Shreya Parasrampuria, SB Infowaves
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Born out of the idea of creating pragmatic and scalable digital solutions, SB Infowaves has been venturing into various realms of technologies like artificial intelligence, machine learning, cloud computing, mobile application development, software development, blockchain technology, and AIoT solutions.
One of the most important drivers of the company's success is the leadership style of Shreya Parasrampuria. She holds professional expertise in fields like finance, strategy, and digital transformation; therefore, she advocates the creation of customer-centric solutions aimed at addressing business problems. Her leadership style is innovative and implementation-driven, which means that companies can implement digital transformation successfully.
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The success of the company within the industry could also be seen during CMPL Expo 2026, where SB Infowaves received considerable attention from visitors due to their AI agents, automation technologies, and performance marketing. This success in terms of visitor interest shows the current market demand for innovations, including AI applications and automation of business processes.
By offering customers innovative solutions and promising business automation, the company continues positioning itself as a reliable partner of digital transformation of various companies all around the world. As a part of the company's vision, one can mention the development of scalable artificial intelligence solutions.
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Custom AI Software Development in India: Rethinking Growth Beyond Traditional IT Giants
For years, companies have been relying on big IT companies such as Tata Consultancy Services, Infosys and Wipro for developing and maintaining their digital infrastructure. In many ways, the companies listed above have a hand in shaping the global technology market today.
But like all business trends, technology evolves. Companies today are demanding faster, smarter, and more adaptable technologies than their current IT models were designed to support.
This change has led to the rapid rise of custom AI software development companies in India-as well as a desire for more agile, results-oriented business technologies.
Why is custom AI development growing?
Instead of selling a standardized product, custom AI development allows businesses to build solutions tailored for specific needs, goals and customer behavior. By developing your solutions in-house and on a unique business level, your technology is designed to perfectly fit your business needs.
Benefits of Custom AI Solutions:
- Built specifically for a certain workflow
- Can be scaled up as the business grows
- Works smoothly with existing business technology
- Can learn and adapt over time to improve.
AI systems are built to evolve over time, and once you deploy them you will not need another business software investment for many years to come.
Limitations of traditional IT involvement
Large IT companies have built credibility with their scale but can be notoriously rigid. This rigidity is a direct problem in today's fast-paced business world.
Businesses have to ask themselves:
- Can the company support quick development and deployment times?
- Are the costs transparent with no hidden costs?
- How customizable are the systems within that cost structure?
- How quickly are the systems being updated to keep up with technologies such as Agentic AI?
For SMEs and startups, rigid processes will only put off market growth.
Emerging agile AI-first companies
The current trend is shifting toward new types of technology partners that leverage both deeply rooted technical know-how and rapid development cycles. This type of partner is able to offer results that go beyond simple project completion.
One example of a company is SB Infowaves, that assists businesses in migrating away from outdated legacy systems and toward the intelligent automated ecosystems they deserve.
SB Infowaves' Competitive Advantages:
- ISO 27001:2022 certified procedures ensure data safety.
- More than 5000 successful projects to their name.
- Expertise in AI, blockchain, cloud, and digital transformation.
- Affordable solutions, ideally for startups and SME businesses.
When combining speed with reliability, there are no limits to what you are able to innovate on.
Driving quantifiable business results with custom AI
The focus of custom AI does not end at implementing technology-it continues at realizing its effects within the business itself.
Companies who embrace AI driven solutions enjoy tangible results such as:
- Cut downtime on processes by as much as 40%
- Higher ROI through smart automation
- Better strategic decision-making based on current business data
As evidenced by Star Cement, Emami Group, and other industry pioneers, these tangible results are becoming increasingly commonplace across all industries.
An example: Transforming media workflows using AI
A specific project involved using state of the art AI technology to speed up the production process of an independent media firm.
The solutions delivered by SB Infowaves include:
- Real-time monitoring for delays in the production pipeline.
- Automated recommendation engines for scheduling resources.
- AI driven audio and video synchronization.
- Real-time data that enables efficient content delivery.
Business improvements were realized in the form of a 30-40% acceleration in the production pipeline, overall better quality, and increased operational efficiency without as much manual effort as previously needed.
This shows a business moving creative processes towards being both more automated and more data-driven.
High-impact use cases for different business segments
Custom AI is proven to be scalable and applicable across a variety of business sectors and sizes.
- Startups: Building MVPs powered by AI, smart recommendation engines, automated on-boarding processes.
- Enterprises: Complete process automation, prediction modeling for maintenance, AI based decision intelligence.
The application of AI does not stop with specific processes or departments-it is implemented across the entirety of the business.
How is SEO and growth improved by AI?
Smart, integrated AI systems increase overall digital performance by facilitating:
- Intelligent customer targeting
- Marketing campaign effectiveness
- Data driven strategic decision making
Companies focusing on the terms "custom AI development company India" or "AI automation services for business" are on the path to success.
Why are businesses turning their backs on the big IT firms?
The shift from outdated legacy IT models toward flexible AI driven companies is driven by specific reasons:
MetricTraditional IT FirmsAI Focused CompaniesFlexibilityLowHighCost EfficiencyModerate- to highOptimizedSpeed of innovationSlowFastCustomizationPoor ExtensiveAI expertiseEmergingCore Strength
This shift signals a new approach to technology within businesses worldwide: moving from the perception of tech support to an integrated growth strategy.
The future is AI Driven Business Transformation
In a more data-driven world, AI will become increasingly central to all business operations and strategy. Upcoming developments include:
- Autonomous AI agents in the workplace.
- Real time decision making powered by data analysis.
- Customer hyper-personalization.
It will benefit businesses greatly to have integrated AI development on the market so that they will be able to maintain their pace and lead within their industry.
Selecting the best technology partner
There is a high dependency of success on a partner who knows not only the intricacies of the technology itself, but also the overall business needs that drive the development of AI systems.
By selecting the right partner SB Infowaves allows businesses to:
- Createintelligent software solutions.
- Automate crucial business processes.
- Efficiently scale operations.
No matter whether a business is trying to launch a new product or streamline an existing service, having a solid technology partner can immensely accelerate the pace of their success.
Final thoughts
In today's fast-paced world of business, you no longer need to focus on competing on scale with organizations such as Infosys or Wipro. Instead, you should be looking at building smarter, faster, and more agile technologies. Custom AI software development is able to provide this very advantage, helping companies to innovate, improve, and drive growth at an efficient pace. And with the right technology partner at your side, this transformation is no longer a distant dream.
Kolkata:
Adventz Infinity, Office No - 1509 BN - 5, Street Number -18 Bidhannagar, Kolkata - 700091 West Bengal
SB Infowaves is in commanding position at CMPL,2026
In a significant development in India’s fast-evolving technology services sector, SB Infowaves, under the leadership of founder and Managing Director Shreya Parasrampuria, is strengthening its global footprint through strategic partnerships, advanced AI-driven offerings, and active participation in major industry platforms.
Founded with a vision to deliver practical, scalable technology solutions, SB Infowaves has grown into a multi-domain digital transformation company offering services across artificial intelligence, machine learning, custom software development, cloud infrastructure, web and mobile applications. The company has positioned itself strongly in emerging areas such as AIoT (Artificial Intelligence of Things), integrating connected devices with intelligent data systems to enable real-time decision-making and automation for businesses across industries.
As the MD, Parasrampuria brings a great combination of finance and strategy, having gained much experience working in PwC and ICICI Bank. She places an emphasis on solving problems and implementing them by creating unique technological platforms. Thanks to her guidance, SB Infowaves managed to increase its delivery across the globe, focusing on the client-centeredness and tangible results.
SB Infowaves is planning to take part in CMPL Expo 2026 that is going to be held between May 4 and June 6, 2026, at Jio World Convention Centre in Mumbai. Being considered as one of the most prominent events for the contract manufacturing and private label sector in Asia, the event is going to be attended by such companies as those involved in the FMCG industry.
The involvement of the firm in the CMPL Expo showcases its attempts at expansion into various sectors such as retail, manufacturing, and e-commerce, where there is an increasing demand for AI-based automation, data analytics, and digitization.
Custom AI Software Development in India: The Smart Choice for Modern Businesses
The international business environment is experiencing a shift as a result of the use of artificial intelligence. Organizations are increasingly opting for artificial intelligence software development in India due to its speed, efficiency, and lower costs compared to working with big IT firms.
The Move from Traditional IT to AI Innovations
Traditionally, IT giants were the go-to option when it came to technology in enterprises. However, such firms have a one-size-fits-all strategy that does not cater to the demands of contemporary enterprises.
Enterprises require:
AI technology designed according to specific industry requirements
Rapid deployment
Adaptive development processes
What Sets Apart Custom AI Solutions?
Custom AI solutions do not follow a template approach but emphasize developing systems suited to your objectives and unique business problems.
The core benefits include:
Development of machine learning models
AI-driven analytics platform creation
Building intelligent automation systems
Enterprise-scale AI software development
Why Hire Indian AI Developers?
India's stature as a technology hub remains unassailable, particularly in areas such as artificial intelligence and automation.
Working with Indian companies allows you to enjoy:
Cost-effective AI development
A pool of expert AI developers
Swift project implementation
World-class delivery options
The Power of AI Automation in Business
No longer an option, but a necessity.
AI automation services for business offer the ability to optimize processes, eliminate human errors, and achieve greater efficiency.
Applications include:
Automated customer service
Smart data analysis
Optimized workflow
Sales and marketing automation
Agentic AI: The Future of AI
One of the groundbreaking technologies in AI is Agentic AI development services.
Unlike AI automation, agentic systems operate autonomously, make decisions, and learn constantly.
With agentic AI services, businesses can:
Future-Ready Businesses
With SaaS and AI, future-ready businesses will be born.
As one of the leading SaaS product development firms in India, SB Infowaves assists companies to develop SaaS products which are:
Scalable
Smart
Customer-centric
Through AI-enabled SaaS systems, companies can provide smarter solutions while keeping up with their competition.
Why SB Infowaves is Your AI Partner?
Through SB Infowaves, you will have access to AI expertise and solutions that match your business goals.
Some of the services provided by them include:
Development of custom AI software
Conclusion
The right technological partner will mean everything for success in the world of artificial intelligence.
With the help of an Indian custom AI software development company, companies will have the advantage they need to succeed.
In addition, SB Infowaves offers much more than services; it is a technological partner in the development of the capabilities of artificial intelligence.
Contact SB Infowaves
📍 India – Kolkata (Head Office)
Adventz Infinity, Office No - 1509 BN - 5, Street Number -18
Bidhannagar, Kolkata - 700091, West Bengal
📞 +91-9804-360-617
📧[email protected]
