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Services that end in production — not PowerPoint.

Four focused offerings. Every engagement starts with a fixed-price discovery sprint and ends with working software you own outright.

2 weeksfixed-price discovery sprint — architecture, roadmap, honest go/no-go
4–6 weeksbuild with weekly demos of working software
8–12 weekstypical path from kickoff to production
100% yourscode, infrastructure & IP — no lock-in

Service 01

Agentic AI Development

Multi-agent systems that plan tasks, call your tools, validate their own outputs, and escalate to humans when stakes are high. Built for real workflows: support resolution, document processing, claims triage, operations coordination.

  • Orchestrated multi-agent architecture — planner, executor, and validator agents with clean handoffs and failure recovery.
  • Human-in-the-loop by design — approval gates on critical actions, not bolted on after a compliance review.
  • Evaluation before deployment — every agent ships with a test suite measuring accuracy, safety, and cost per task.
Deep dive: how we build agents →

Best for

  • High-volume repetitive workflows (support, back office, document handling)
  • Processes with clear rules but messy inputs
  • Teams drowning in coordination work across systems

Typical timeline

8–12 weeks from discovery to production.

Service 02

Agent Infrastructure Engineering — MCP, A2A & the open agent stack

Enterprise agents in 2026 run on open standards: MCP (now Linux Foundation–governed) for agent-to-tool access, Google's A2A for agent-to-agent coordination, and AP2 emerging for agent payments. We engineer this layer for your stack — so your AI investment survives every model and vendor shift.

  • Custom MCP servers for proprietary and legacy systems that no off-the-shelf connector covers.
  • A2A-based multi-agent coordination — your agents and your vendors' agents collaborating across organisational boundaries.
  • Least-privilege access control — agents get exactly the permissions a task needs, nothing more.
  • Full audit logging — every tool call recorded, queryable, and compliance-ready.
  • Model-agnostic — the same integration layer works with Claude, GPT, Gemini, or self-hosted models.

Best for

  • Enterprises with legacy systems AI can't currently touch
  • Teams standardizing AI access across many tools
  • Security-conscious orgs that need scoped, logged AI actions

Typical timeline

2–6 weeks per integration depending on system complexity.

Service 03

Pilot-to-Production Engineering

You built a promising AI prototype — internally or with another vendor — and it's been stuck for months. We audit it, keep what works, and engineer the missing 80%: evaluation, guardrails, monitoring, and deployment.

  • Production audit — a structured review of your pilot's architecture, prompts, data flow, and failure modes.
  • Evaluation harness — measurable quality gates so "is it good enough?" stops being a matter of opinion.
  • Guardrails & governance — input/output filtering, action limits, audit trails, rollback paths.
  • MLOps & monitoring — cost tracking, drift detection, alerting, and retraining pipelines.

Best for

  • Pilots stalled 3+ months without a path to deployment
  • Teams facing security/compliance blockers on AI rollout
  • Leaders who need to show ROI on AI spend this year

Typical timeline

Audit in 2 weeks. Hardening in 4–8 weeks.

Service 04

AI-Native Product Engineering

Add AI capabilities to your existing product — copilots, RAG-powered search, intelligent recommendations, automation — without a rewrite. Or build a new AI product with us from zero to launch.

  • Copilot & conversational interfaces embedded in your product, grounded in your data.
  • RAG done right — retrieval pipelines with chunking, reranking, and evaluation, not naive vector search.
  • Full-stack delivery — backend, frontend, infrastructure, and the AI layer as one accountable team.

Best for

  • SaaS companies adding AI features competitors already ship
  • Founders building AI-first products who need a senior team fast
  • Enterprises modernizing internal tools

Typical timeline

MVP in 6–10 weeks; ongoing product partnership available.

Not sure which engagement fits?

Start with the free AI Readiness Assessment — we'll tell you which of these (if any) makes sense for where you are.

Get Your Free Assessment