We don’t just run your tech stack. We redesign it for agents.
Agents are only as good as the systems they can reach and the data they can trust. We develop and maintain your applications, modernize the core, wire everything together, and make your data agent-ready—the foundation the whole operating system stands on.
Systems, Applications, and Data Engineering
- Run and reengineer—we keep applications running and modernize them for agents
- Systems agents can reach—legacy cores integrated through a clean backbone
- Data agents can trust—pipelines and a cloud foundation that are agent-ready
- GCCs, transformed—capability centers shifted from running software to running intelligence
Why It Matters
The agentic era runs on a stack that wasn’t built for it
We engineer the foundation—so the intelligence on top has something solid to stand on.
Your core systems were built for human operators and batch processes—not for agents that need to read state, take action, and be trusted in real time. Most agentic pilots don’t stall on the model. They stall on the plumbing.
Your core systems were built for human operators and batch processes—not for agents that need to read state, take action, and be trusted in real time. Most agentic pilots don’t stall on the model. They stall on the plumbing.
Out of reach
Agents can’t touch the core
Claims engines, billing platforms, loan systems: locked behind brittle interfaces an agent can’t use safely or reliably.
Not agent-ready
Your data isn’t ready
Scattered, inconsistent, and undocumented: fine for a report, not for an agent making a decision in the moment.
Maintenance ≠ modernization
Keeping the lights on isn’t enough
A maintained legacy stack is still a legacy stack. The agentic era needs the foundation reengineered, not just patched.
WHAT WE ENGINEER
From application to data to cloud—rebuilt for agents.
The full-stack engineering that turns a legacy estate into an agent-ready operating environment, built and run by the same team.
Operational data, not model data. Training data, labelling, and synthetic data sit with the model lifecycle. Here we engineer the data your operation runs on.
Operational data, not model data. Training data, labelling, and synthetic data sit with the model lifecycle. Here we engineer the data your operation runs on.
01
Application development & maintenance
We build new applications and run existing ones, including product engineering, with the same team that reengineers them for agentic era.
02
Core and legacy modernization
Modernize the platforms your operation depends on, claims, billing, lending, core admin, so they can be reached, automated, and trusted.
03
Integration & API/event backbone
A clean, event-driven backbone that connects legacy systems and gives agents safe, real-time access to act, not screen-scraping.
04
Quality and test engineering
Automated testing and release engineering, because an agentic operation changes constantly and still has to stay correct.
05
Data pipelines and cloud foundation
The operational data plumbing and cloud-native base the operation runs on that's reliable, observable, and built to scale.
06
Data readiness for agents
Operational data made consistent, accessible, and trustworthy enough for an agent to act on it. This is the difference between a report and a decision.
For capability centers
Already run a GCC? We bring the agentic era to it.
Capability centers were built to do work at lower cost. The next move is to make them run intelligence. And that’s a reengineering job, not a staffing one.
Beyond staffing
We don’t just fill seats. We stand up data scientists, AI engineers, full-stack developers, and enterprise IT under one roof. We provide a capability, not a labour pool.
Talent plus the tech to use it.
Re-engineer the stack
Modernize the applications and data the center runs, and rebuild its processes around agents. The center compounds intelligence, not headcount.
Run intelligence, not just software.
AI Centers of Excellence
Embed the engines, governance, and reusable assets that let the center keep improving. Build-Operate-Transfer when you want to own it outright.
Yours to keep, when you’re ready.
proof in production
Legacy estates re-engineered
Most agentic ambition dies in the integration layer: the ageing core systems an agent can’t reach. Here are a couple of estates we modernized, integrated, and now run.
Banking | Legacy modernization and integration
Multi-system integration and automation
A UK banking group’s finance operations ran on an ageing legacy estate across 8 sites. We integrated the systems and put a 125-bot digital workforce into production.
Intelligent automation used to solve multi-system integration: 0% operational disruption, and 0% downtime since go-live.
Intelligent automation used to solve multi-system integration: 0% operational disruption, and 0% downtime since go-live.
25%
lower cost to serve, contractually guaranteed
125 bots
across an 8-site legacy estate
+31→+45
NPS improvement
Education and assessment | Global capability center
GCC build and scale up
A capability center, not a labor pool that runs engineering, data, and IT operations under one roof, set up and scaled fast.
Designed to shift from running software to running intelligence with Build-Operate-Transfer on the table.
Designed to shift from running software to running intelligence with Build-Operate-Transfer on the table.
70+
specialist technical roles stood up
Full-stack
data science, AI/ML, dev & enterprise IT
BOT
Build, operate, transfer optional
full-stack operator
Intelligence That Operates
The foundation feeds every layer above it, and usually starts with a clear-eyed look at the operating model.
WHERE IT OFTEN STARTS
Operating-model & tech-stack design
Modernization works best when it follows a target operating model. The strategy and the business case come first.
Explore consulting
The models behind the signal
Sensor and operations intelligence
Once systems are reachable, sensors turn them into live signal. This is the start of the operations-intelligence loop.
Explore how sensors turn into operational intelligence
Good questions to start with
Do you do traditional application development and maintenance, or only AI work?
Both — and we don’t treat them as separate. We run and maintain your applications, and the same team reengineers them for the agentic era. The point isn’t to keep legacy alive; it’s to modernize it into something agents can use.
Do we have to rip and replace our core systems?
No. We modernize and integrate what you have, wrapping legacy cores in a clean backbone that gives agents safe, real-time access. We replace only where replacing is genuinely the right call.
What does “data readiness for agents” actually mean?
Making your operational data consistent, accessible, and trustworthy enough for an agent to act on in the moment — not just accurate enough for a monthly report. It’s the plumbing, not the model’s training data.
Can you transform our existing GCC or capability center?
Yes. We bring agentic-era transformation to existing centers — modernizing the stack, standing up AI Centers of Excellence, and shifting the center from running software to running intelligence, with Build-Operate-Transfer if you want to own it.
Is this the same as your AI Data Services?
No. Here we engineer the systems, applications, and operational data your operation runs on. Building, fine-tuning, and evaluating the AI model — and its training data — is something we do as your data services partner.
INSIGHTS
Latest from the Firstsource team
Insights from the field, real operations, real outcomes, and perspectives from the people making it work in live operations.
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Contact US
Scope an engagement
Tell us where you want to start—a single layer, a full operating-system build, or operating what you already run. We’ll show you where the economics change first.
- Engineer one layer, or the whole operating system
- Reengineer an existing GCC or capability center
- Operate the system to an outcome, under one contract