#govtech

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Cryptocurrency, blockchain, and Distributed Ledger Technology (DLT) have been disrupting industries and challenging traditional business models since their inception. These technologies have the potential to revolutionize the way we do business, interact with each other, and even govern ourselves. In this blog post, we will explore the disruptive potential of cryptocurrency, blockchain, and DLT.

Cryptocurrency

Cryptocurrency, such as Bitcoin and Ethereum, is a decentralized digital currency that uses cryptography to secure transactions and control the creation of new units. Cryptocurrency has the potential to disrupt traditional financial systems by providing a more secure and transparent way to transfer value. Cryptocurrency eliminates the need for intermediaries, such as banks, and can help reduce transaction fees and increase financial inclusion.

Blockchain

Blockchain is a distributed ledger that records transactions in a secure and transparent way. Each block in the chain contains a cryptographic hash of the previous block, creating an immutable record of all transactions on the network. Blockchain has the potential to disrupt a wide range of industries, including finance, healthcare, and supply chain management. Blockchain can help increase transparency, reduce fraud, and improve efficiency.

Distributed Ledger Technology (DLT)

DLT is a type of database that is distributed across a network of computers. Each computer in the network has a copy of the database, and any changes to the database are recorded in a transparent and immutable way. DLT has the potential to disrupt a wide range of industries, including finance, healthcare, and government. DLT can help increase transparency, reduce fraud, and improve efficiency.

Disruptive Potential

The disruptive potential of cryptocurrency, blockchain, and DLT is significant. Here are some of the ways that these technologies could disrupt traditional industries: Finance Cryptocurrency and blockchain have the potential to disrupt traditional financial systems by providing a more secure and transparent way to transfer value. Cryptocurrency eliminates the need for intermediaries, such as banks, and can help reduce transaction fees and increase financial inclusion. Blockchain can also help reduce fraud and increase transparency in financial transactions. Healthcare

Blockchain and DLT have the potential to disrupt the healthcare industry by providing a more secure and transparent way to store and share patient data. Blockchain can help increase patient privacy and reduce the risk of data breaches. DLT can also help improve the efficiency of healthcare systems by reducing administrative costs and improving supply chain management.

Government

DLT has the potential to disrupt traditional government systems by providing a more secure and transparent way to store and share data. DLT can help increase transparency and reduce fraud in government transactions. DLT can also help improve the efficiency of government systems by reducing administrative costs and improving data management.

Conclusion

Our working style also incorporates agile sprint planning.

The first two weeks

We spent the first two weeks with our partners getting oriented, and doing free-form discovery; talking with folks, reading documents, reviewing previous research, trying to understand the problem space and organizational context, and getting situated.

We didn’t plan formal sprints; instead we created one Trello board for each week and added tasks as they emerged.

Halfway through this time, I learned about Sprint 0 from Cohort 2 #CodeForCanada PM fellow Siobhan.

Have you had any luck with Sprint 0? Is it useful?

Instead of Sprint 0, we used Sprint 1 to learn how to sprint as a team. We filled and prioritized the backlog, planned the sprint, updated and provided visibility throughout, and reviewed the sprint and did a retrospective together, continuously checking in with one another.

Although we did include substantial tasks, we were kind to ourselves if things were left incomplete.

Sprint planning schedule

Since then, we’ve been on a bi-weekly sprint schedule. The sprint schedule goes as follows:

[Ongoing] Gather activities for the backlog

[Sprint Day 1 - Monday] Sprint planning meeting

[Daily] Standup at 9:45am

[Sprint Day 10 - Friday] Sprint retro

How do you organize your sprint planning meeting, daily standup, and sprint retro meeting? When do you schedule them? What format works best for your team?

Sprint planning tools

We use Trello to build the backlog and tee-up the sprint tasks. This has a simple and straightforward Kanban format – backlog, todo, doing, done.

We tried a couple other Kanban mediums – colourful sticky notes & sharpies and writing on a whiteboard.

Although these are great for in-office visibility, ultimately Trello is our source-of-truth because it enables remote work and is accessible on mobile.

What tools or software do you use for sprint planning and tracking?

Maintaining and prioritizing the backlog

Since we’re still in discovery, our backlog tasks have been exploratory and high-level. For example, “map the policy landscape” or “build a framework to prioritize problems”.

I often refer to these as “choose-your-own-adventure” activities. In almost all cases, the person who proposed the activity was accountable for ensuring it got done. They had the best idea of how to approach the activity – whether it was individual research, a sticky-note workshop with the team, or setting up stakeholder interviews. But the approach became more visible as new information was uncovered.

Because these were mostly led by individuals, there hasn’t been much backlog maintenance or prioritization thus far.

At the beginning of a project, how do you balance your team’s excitement for individual initiatives and investigation, and prioritizing a backlog?

Looking forward

Change is inevitable. As our project progresses, we’ll reassess what works and what doesn’t, and adapt from there.

As we move into experimentation, our activities will become more concrete in scope and tasks. Our tasks will likely have to be estimated and the backlog groomed; priorities clearly communicated to ensure the team is aligned and moving in the same direction.

In today’s world, digital transformation is essential. Governments worldwide are using technology to streamline operations, improve transparency, and provide better services to citizens. Leading this change is Unwind Learning Labs Pvt Ltd (in22labs), an innovative E-governance solutions provider based in Chennai and Vijayawada, India.

The company is expanding its presence in the USA, Africa, and the Middle East, including countries like Rwanda, Namibia, Kenya, Tanzania, Morocco, Qatar, Oman, and Abu Dhabi. 

This blog examines how modern E-governance solutions are changing public administration and why governments in different regions are heavily investing in digital infrastructure. 

What Is E-Governance and Why Does It Matter? 

E-governance involves using information and communication technology (ICT) to provide government services, share information, and carry out transactions between government entities and citizens, businesses, and other organizations. It shifts bureaucracy from paper processes to digital platforms. This change helps reduce corruption, speeds up delivery, and holds governments accountable. 

The benefits are significant:

Speed: Tasks that once took weeks now take hours. 

Transparency: Every action is recorded, making it easy to audit and trace. 

Accessibility: Citizens in rural areas can access services without needing to visit government offices. 

Cost Efficiency: Digital processes greatly reduce operating costs. 

The in22labs Approach to E-Governance 

At in22labs, we do more than just create software; we create ecosystems. Our complete set of E-governance tools addresses all aspects of government administration, including education, finance, environment, and fisheries. Here’s a snapshot of what we offer:

LMS Suite Software: Digitizes learning and training for government employees and citizens. 

Social Welfare Suite Software: Manages beneficiary data, welfare programs, and distribution systems. 

E-Office & File Management System Software: Introduces paperless administration in government offices. 

Vendor & Bill Management System Software: Automates procurement, vendor evaluations, and billing processes. 

GIS & Tagging Solutions Software: Provides location intelligence for infrastructure and resource mapping. 

Dashboard & Analytics Solutions Software:Offers real-time data visualization for informed decision-making. 

Finance & Audit System Software: Assures financial accountability and audit readiness. 

Fisheries & Inland Water Management System Software:Supports the sustainable management of aquatic resources. 

Pollution Control and Environment System Software: Helps monitor and manage environmental compliance. 

 Managed Cloud Solutions Software: Delivers secure, scalable cloud infrastructure for government data. 

Mobile App Development Services: Creates citizen-facing apps for easy access to government services. 

E-Governance Across Borders: India, Africa, and the Middle East

India 

In Chennai and Vijayawada, in22labs has implemented solutions that have changed how state departments handle files, finances, and citizen welfare.

Tamil Nadu's complicated social welfare system, for example, benefits from our Social Welfare Suite Software, which tracks beneficiaries, manages eligibility for schemes, and ensures there is no leakage in benefit distribution. 

Africa  

The African continent is witnessing a governance technology transformation.

Countries such as Rwanda, Kenya, Tanzania, Namibia, and Morocco are rapidly investing in digital public infrastructure. in22labs has teamed up with African governments to use GIS & Tagging Solutions Software for land management, Dashboard & Analytics Solutions Software for national KPI tracking, and Managed Cloud Solutions Software for secure e-governance hosting. 

Middle East 

In Qatar, Oman, and Abu Dhabi, governments are pursuing ambitious smart city and digital transformation goals.

Our E-Office & File Management System Software and Finance & Audit System Software help ministries and municipalities achieve seamless, paperless, and audit-ready operations. 

The Road Ahead 

In the coming decade, E-governance will likely be the foundation of all public administration. AI-powered analytics, real-time dashboards, mobile-first designs, and cloud-based infrastructure will shape future governments.

in22labs is already working on that future, one solution at a time. 

Whether you are a national ministry in Kenya, a state department in Andhra Pradesh, or a municipality in Oman, our team is ready to collaborate on your digital governance journey. 

Land acquisition projects often face delays, scattered documentation, communication gaps, and reporting challenges.

LAMS (Land Acquisition Management System) is built to simplify and digitize the complete process through a centralized web-based platform that improves transparency, accountability, and operational efficiency.

The landscape of government contracting and IT staffing is undergoing a seismic transformation. At the center of this shift stands HBITS NY — New York State's Hourly Based IT Services program — which has long served as the backbone of how state agencies procure technology talent. Now, with generative AI reshaping virtually every corner of the tech industry, the program faces both extraordinary opportunities and significant challenges that demand careful navigation.

Understanding the HBITS NY Framework

Before diving into the AI dimension, it's essential to understand what HBITS NY represents. The program is a competitively awarded contract vehicle that allows New York State agencies to engage IT professionals across dozens of labor categories — from project managers and systems architects to cybersecurity analysts and data scientists. Vendors compete for placement on the contract, and agencies then use it to quickly source skilled technology workers without going through a full competitive procurement each time.

The program has historically been celebrated for its flexibility and speed. It reduces administrative burden while giving agencies access to a broad, pre-qualified talent pool. However, the rise of generative AI is prompting a rethinking of what "skilled IT talent" actually means — and whether the existing labor categories and rate structures adequately reflect today's market realities.

New Roles Emerging from Generative AI

Generative AI has given birth to an entirely new class of IT roles that simply did not exist a few years ago. Prompt engineers, AI model trainers, LLM fine-tuning specialists, retrieval-augmented generation (RAG) architects, and AI ethics auditors are just a sampling of the positions now in high demand across state agencies. These roles sit at the intersection of data science, software engineering, and domain expertise — a combination that traditional labor classifications struggle to accommodate.

For HBITS NY to remain a relevant and effective procurement vehicle, it must evolve to incorporate these emerging titles. Agencies piloting generative AI tools for citizen services, document automation, and fraud detection need contract structures that reflect the nuanced skills required. Without updated labor categories, agencies may be forced into misclassifying contractors or pursuing alternative procurement routes — both of which introduce inefficiencies and compliance risks.

Challenges in Rate Structures and Talent Competition

One of the most pressing challenges is compensation. Generative AI specialists command premium salaries in the private sector, and government rate structures have historically lagged behind market rates. If the hourly billing rates within the HBITS framework cannot keep pace with commercial compensation expectations, the state risks being unable to attract top-tier AI talent to critical public sector projects.

Vendors participating in the program must also grapple with the rapid pace of skill obsolescence. A professional certified in a particular AI platform today may find those skills outdated within 18 months as the technology evolves. This creates pressure on both vendors and agencies to build continuous learning expectations into their engagements — a concept that traditional staffing contracts are ill-equipped to handle.

Governance, Ethics, and Accountability

Perhaps the most complex challenge lies in governance. When AI systems make or inform decisions affecting citizens — from benefit eligibility to public safety — questions of accountability become paramount. State agencies deploying generative AI through contractors sourced via HBITS NY must clearly define who is responsible when an AI system produces biased, erroneous, or harmful outputs. The contract language, deliverable definitions, and performance metrics used in traditional IT staffing do not naturally extend to AI-driven outcomes.

New York State has already begun exploring AI governance frameworks, and HBITS-sourced contractors are increasingly expected to work within these evolving guidelines. This includes adhering to data privacy regulations, documenting AI model decisions for audit purposes, and ensuring that AI tools meet accessibility standards required under state law. Vendors must proactively build these compliance capabilities into their teams.

The Path Forward

Adapting to the generative AI era requires proactive collaboration between the Office of General Services (OGS), state agencies, and participating vendors. Key steps include modernizing labor category definitions to include AI-specific roles, conducting regular market rate analyses to maintain competitive compensation ceilings, and developing clear ethical and legal guidelines for AI deployments sourced through the contract.

Training and upskilling must also become a shared priority. Agencies should consider building professional development clauses into task orders, encouraging contractors to maintain current AI certifications throughout their engagements. Similarly, vendors should invest in AI literacy across their workforce — not just among specialists, but across all IT roles, as generative AI tools increasingly augment everyday technology work.

Conclusion

Quick reality check on AI in regulated industries:

→ Loan decisions at JPMorgan: AI → Radiology scans across 74% of US hospitals: AI → Citizen-services chatbots handling millions of public queries: AI

And the money behind it is already locked:

FinTech AI market: ~$66.5B by 2030

Healthcare AI market: $505B by 2033

~90% of US federal agencies adopting or planning AI

EU AI Act medical-AI rules start in 2026

Here's the part most teams get wrong. They treat AI like a feature — bolt it on, ship it, move on. The companies actually winning treat it like a system: data governance, compliance, and human oversight built in from day one. Because in a regulated industry, the moment something goes wrong, every shortcut is auditable.

The real question for any team is build, buy, or partner. Build in-house only for the IP that differentiates you. Buy off-the-shelf for the generic stuff. Partner for the high-stakes workflows where a wrong answer costs money, lives, or public trust.

Empiric Infotech put together this guide on AI in regulated industries — forecasts to 2030/2033, the 2027 compliance wave, real deployment examples, and the full decision framework. Worth a read if your business is anywhere near banking, healthcare, or the public sector.