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SERVICE

AI Agents

Task-focused systems that read text, use tools, and call other APIs — designed for the complex parts of your team's day-to-day operations.
THE POSITION

An agent is only useful when it can actually do the work, safely.

A chat interface bolted onto a knowledge base is not an agent. Value appears when a system can retrieve the right context, call the right tool, and complete a task end to end.

We build agents with a narrow mandate, an explicit tool surface, permission scoping per user, and a defined stopping condition.

CAPABILITIES

What the engagement includes

01
Tool design

Each capability is a typed, permissioned tool with validation, not an open shell.

02
Grounded retrieval

Answers are traced to source documents and records.

03
Session memory

Agents keep task state without leaking context between users or tenants.

04
Evaluation harness

Behaviour is tested against a growing suite of real cases before release.

SYSTEM ARCHITECTURE

How the system runs end to end

REFERENCE FLOW
01
Intent

The agent classifies what is being asked and whether it is in scope.

02
Retrieve

Relevant records and documents are grounded into the context.

03
Plan

A short, inspectable plan of tool calls is produced.

04
Act

Tools execute against permissioned APIs.

05
Verify

Results are checked against expected shape and policy.

06
Hand back

The agent completes, escalates, or asks one clarifying question.

TECHNOLOGY

Typical stack

TypeScript Python LangGraph pgvector Redis OpenAI Anthropic OpenTelemetry
OUTCOMES
Scoped autonomy

Agents act where they are permitted, and stop where they are not.

Traceable answers

Every response can be traced back to a source.

Faster resolution

Routine tasks complete without a queue.