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What we build

Four things we get asked for

Autonomous workflow and task agents

AI systems designed to execute multi-step business processes independently. From processing documents and triaging customer support tickets to managing internal workflows, agents reduce manual effort and remove operational bottlenecks.

Retrieval-augmented assistants

Enterprise assistants grounded in your internal documentation, knowledge bases and databases. Teams can query proprietary data with citations back to the source, under access controls that match the permissions they already have.

Multi-agent orchestration

Environments where specialised agents collaborate — passing data, calling tools and verifying each other’s output — to handle work like research, lead scoring, and financial analysis.

Custom AI integration and fine-tuning

Foundation models connected directly to your APIs, CRM, ERP and databases, with behaviour tuned to your domain. We are explicit about when fine-tuning is worth the cost and when prompting and retrieval are enough.

Core technologies

How it is built

Reasoning and generation

Commercial foundation models

Hosted frontier models for comprehension, structured output and tool use. Best when accuracy matters more than unit cost and your data terms permit it.

Orchestration

Agent frameworks

Libraries for context management, tool use and prompt pipelines. We use the lightest one that solves the problem rather than the most capable one.

Data residency and cost control

Self-hosted and fine-tuned models

Open-weight models hosted in your own environment, with custom embeddings, targeted fine-tuning and safety guardrails for the specific domain.

How we deliver

Our implementation process

  1. Readiness and use-case mapping

    We review your workflows and data infrastructure to find where automation actually pays for itself, and where it does not.

  2. Architecture and guardrail design

    System prompts, retrieval design, tool permissions and safety guardrails are agreed before any agent is built.

  3. Engineering and integration

    We build the agents and connect them to your web or mobile applications through your own APIs.

  4. Evaluation and testing

    Edge cases, output quality, latency, per-run cost and reliability are measured and reported, not assumed.

  5. Deployment and monitoring

    Agents ship with telemetry, cost tracking and a feedback loop, so you can see what they are doing and what they cost.

Next step

Find out where automation would pay off

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