From point solutions to agentic operations
Running real work takes many agents, your people, and your systems acting as one—reliably, on any vendor’s model, and safely enough for production. We engineer that orchestration, and we run it.
Agentic Orchestration
- Many agents, one workflow—orchestrated across front, middle, and back office
- Humans + agents together—work handed off cleanly, both in the loop
- Vendor-agnostic—your choice of model and agent platform, swappable
- Production-grade—built to recover, not just to demo
Why It Matters
Demos are easy. Operations are hard.
We orchestrate agents, people, and systems into one operation that holds up.
A single agent answering a single question looks magical. An operation is a different problem: dozens of agents and people, across many systems, handling exceptions, under compliance, all day. That’s an orchestration and engineering challenge—and it’s where most pilots break.
A single agent answering a single question looks magical. An operation is a different problem: dozens of agents and people, across many systems, handling exceptions, under compliance, all day. That’s an orchestration and engineering challenge—and it’s where most pilots break.
Brittle by design
Single agents fall over
String a few prompts together and the first unexpected case breaks the chain. Real work needs agents that recover, retry, and escalate.
Lock-in
Bet on one vendor, lose optionality
Hard-wire to one model or platform and you’re stuck when the next better one arrives—which, right now, is every few months.
Hand-off chaos
Humans and agents trip over each other
Without clean orchestration, work falls between agent and human—or both touch it, and neither owns it.
WHAT WE ENGINEER
The fabric that turns agents into an operation
We build and orchestrate the agents, the integrations they need, and the workflows that braid agents and people together — on your choice of model and platform. We instrument your operation five ways, fuse the streams into one signal, and feed it into your institutional memory — built on your stack, running the tools you already have.
01
Multi-agent orchestration
Many specialized agents coordinated into one workflow—planning, delegating, escalating, and recovering across a real process.
02
Vendor-agnostic agent fabric
A layer that lets you run any model or agent platform—and swap them—without rewriting the operation around them.
03
Runtime and tool integration
Agents connected to the systems and tools they need to act—through scoped, least-privilege access, not blanket credentials.
04
Front, middle and back-office agents
Agents built for your actual work—discovery, triage, scheduling, payments, complaints, case handling—not generic assistants.
05
Human + AI workflow design
Clean hand-offs between people and agents, with the human in or on the loop—so accountability never falls through the gap.
06
Low-code and citizen enablement
Tooling that lets your own operators build and adjust workflows safely—so the operation keeps improving without an engineering ticket.
How we build agents that don’t fall over
Engineered for production, not for demos
A handful of design principles separate an agent that survives a real operation from one that works until it doesn’t.
Separate and swappable
Reasoning, tools, and memory are independent components—any one can be replaced without rewriting the others.
No single point of lock-in.
Stateless and recoverable
Agent processes hold no state; everything durable lives in your context layer. If one fails, another resumes from the last checkpoint.
It picks up where it left off.
Traceable and least-privilege
Every action is logged and reconstructable; agents never hold blanket credentials—access is scoped to the task.
Safe to run in regulated work.
Whitepaper
Why agents need more than a model to act
Learn about the intelligent context framework, the difference between an intelligent agent and a scripted bot.
proof in production
A pension operation, rebuilt around agents
A major pensions & benefits administrator was running voice-dominant, agent-centric support on legacy infrastructure. We re-platformed it and orchestrated an AI-led operating model—agents and people, one workflow.
Pensions and Benefits | Customer Operations
AI-led customer operations
From voice-dominant and knowledge-from-memory to digitally assisted, AI-augmented, and self-served—on a cloud-native foundation.
Automated identity & verification, auto after-call summarization, member-context auto-population, and smart routing across retirement, bereavement and transfer-out journeys.
Automated identity & verification, auto after-call summarization, member-context auto-population, and smart routing across retirement, bereavement and transfer-out journeys.
300+
member journeys streamlined into 9 flows
65+
processes across several back-office functions
9
legacy systems integrated into one console
75%
increase in digital engagement
20%
faster resolution time
full-stack partner
Intelligence That Operates
Orchestration sits at the top of the stack—governed, informed, and model-agnostic by design
What governs the agents
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Domain harness engineering
Agents act within the skills, playbooks, and guardrails your harness defines—the reason they handle your edge cases safely.
Explore the capability
What informs them
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Context and knowledge engineering
Agents draw on the institutional memory in your context layer, so every action starts with the full picture.
Explore the capability
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Good questions to start with
Which agent platforms do you use to build agents?
Our teams have built agentic systems using a broad variety of industry-leading pro-code and low-code agentic platforms. We'll meet you where you are, help choose agentic design studios, runtime architectures, and get you going.
What keeps agents reliable in a real operation?
Engineering discipline: agents that recover from failure, hold no fragile state, carry least-privilege access, and log every action. And they act within the guardrails your domain harness defines—so “reliable” isn’t a hope, it’s designed in.
How do humans and agents share the work?
We design the hand-offs explicitly. Humans stay in or on the loop, work routes to the right place first time, and accountability is always clear—no task falls between an agent and a person.
Can you orchestrate agents we’ve already built or bought?
Yes. We integrate and orchestrate your existing agents and platforms under one operation—and run it. The constant is Kairos sitting above.
Do you build the AI model itself?
We don’t pre-train or post-train foundation models ourselves. We help you do that as your data services partner—see AI Data Services. Orchestration runs whatever model you choose.
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