Skip to content

Agent Engineering

AI Agent Development

We design and build custom AI agents that perform multi-step work using models, tools, data, APIs, business applications and controlled actions.

TRACEai-agent-development
  1. 01INTENTThe goal arrives from a user, an event or another system.
  2. 02CONTEXTThe agent gathers the data and knowledge it needs.
  3. 03MODELIt reasons through the next step.
  4. 04TOOL.CALLIt acts through a defined, permissioned tool.
  5. 05APPROVALSensitive actions wait for a person.
  6. 06RESULTThe work is completed, traced and evaluated.
6 STEPSTRACE.COMPLETE

What it is

An AI agent is not an LLM with a prompt. It is a system that understands a goal, reasons through a task, uses tools, reads and writes the business data it needs, and takes controlled actions inside defined policies.

We start from the work, not the model: what the task is, who does it today, which decisions and systems are involved, which actions can be automated and which need approval. Where a problem is better solved by deterministic software, we say so. The agent is positioned around the work it performs.

When you need it

  • SIGNAL 01A task is multi-step, repetitive and currently done by people moving between systems.
  • SIGNAL 02You need an agent that acts in your business applications, not a chat window that answers questions.
  • SIGNAL 03Your team has a working prompt, but no agent that can be trusted with real tools.
  • SIGNAL 04The agent must hand off to a person when it reaches the edge of its authority.

What we build

The engineering.

  • 01

    Task-based and autonomous agents

    Agents scoped to a job, from a single well-bounded task to long-running work that plans and executes over many steps.

  • 02

    Tool-using agents

    Agent tool calling against your APIs, databases and business applications, with every action it can take defined up front.

  • 03

    Conversational and customer-facing agents

    A conversational interface connected to the underlying workflow, so the agent can resolve a request, not only reply to it.

  • 04

    Human-in-the-loop agents

    Approval steps and escalation paths wherever an action needs a person to sign it off.

  • 05

    Agent state and memory

    Short-term state for the task in flight and longer-term memory where the work actually benefits from it.

  • 06

    Internal and enterprise agents

    Agents for operations, engineering, research, finance and knowledge work inside the organisation.

How it works

One run, end to end.

  1. 01

    INTENT

    The goal arrives from a user, an event or another system.

  2. 02

    CONTEXT

    The agent gathers the data and knowledge it needs.

  3. 03

    MODEL

    It reasons through the next step.

  4. 04

    TOOL.CALL

    It acts through a defined, permissioned tool.

  5. 05

    APPROVAL

    Sensitive actions wait for a person.

  6. 06

    RESULT

    The work is completed, traced and evaluated.

What it integrates with

Chosen for the workload and your environment — not a preferred provider.

  • APIs
  • Function tools
  • MCP servers
  • Databases
  • CRM and ERP
  • Ticketing
  • Internal APIs
  • Search
All capabilities

In production

Production is part of development.

Evaluation, security, deployment and operations begin before release — on this service as on every other.

EVAL

How we test it

  • Task-success evaluation against the work the agent is meant to do.
  • Tool-use testing, including correct tool selection and call accuracy.
  • Regression tests that run on every change to prompts, tools or models.

POLICY

How we secure it

  • Least-privilege permissions for every tool the agent can call.
  • Human approval gates on actions that should not be automatic.
  • Guardrails and prompt injection testing before release.

RUNTIME

How we deploy it

  • SaaS, private, self-hosted or on-premises, as the environment requires.
  • Agent and model versioning with a tested rollback.

TRACE

How we operate it

  • Traces of every model call, tool call and handoff.
  • Cost, latency and success rate tracked per task.

What you receive

Engineering outputs, not a deck.

We do not hand over a prototype and leave production engineering to you.

  1. 01A working agent in your environment, built around the task it performs
  2. 02Agent architecture and tool definitions, documented
  3. 03An evaluation suite with a golden dataset for the task
  4. 04Permission model and approval gates for every action
  5. 05Tracing and monitoring wired in before release
  6. 06A release pipeline with versioning and rollback