Services
AI Integration & Business Automation
We focus on engineering integrations that fit your systems: API orchestration, retrieval workflows, admin tooling, and monitoring — not hype-driven feature lists.
Who it is for
Teams adding AI without losing control
This service suits organisations exploring large language model features, document automation, or workflow orchestration that must respect security, auditability, and human oversight. Buyers include product leaders, operations directors, and engineering teams evaluating vendor claims.
We are a fit when you need engineering integration — APIs, admin tools, logging — not slide decks about AI strategy alone.
Typical problems
Manual work and disconnected tools
Teams may copy information between systems, manually classify inbound requests, or run ad hoc scripts that nobody maintains. AI vendors promise magic but leave integration, evaluation, and cost control as your problem.
We connect models to your data through deliberate pipelines, with guardrails, fallbacks, and monitoring so automation fails safely rather than silently.
What is included
Practical integrations and operability
Work can include LLM API integration, retrieval workflows, prompt and tool orchestration, human-in-the-loop review UIs, cost and usage logging, and security review of data flows. We document operational playbooks so support teams know how to diagnose issues.
We do not invent performance statistics or guarantee model outputs for regulated decisions without human review where your policy requires it.
Timeline
Typical engagement length.
A scoped integration pilot often runs four to eight weeks including workflow design, engineering, and evaluation hooks. Broader automation programmes are phased after a successful pilot demonstrates measurable time savings or quality improvement.
How it works
From discovery call to delivery.
We start from operational pain — what manual work exists, what data is available, what must stay human-reviewed — then design integrations that fit your systems. Pilots have explicit success criteria before production rollout.
FAQ
Common questions.
Do you train custom models?
Most engagements integrate established model APIs and retrieval over your approved data sources. Custom training is scoped separately when there is a clear business case and data governance in place.
How do you manage API cost?
We implement logging, quotas, caching where appropriate, and workflow design that avoids unnecessary token use. We help you understand cost drivers before scaling traffic.
Can AI read our confidential documents?
Only within architectures you approve. We review data residency, retention, and access controls, and we prefer patterns that minimise exposure of sensitive content to external services when your policy requires it.
What about accuracy and hallucinations?
We design human review steps, structured outputs, and evaluation checks for high-risk paths. Fully autonomous decisions are avoided unless you explicitly accept the residual risk after testing.
Do you replace our existing automation tools?
Not necessarily. We often integrate with CRMs, ticketing systems, or iPaaS tools you already pay for, adding engineering where off-the-shelf connectors are insufficient.
Ready to talk?
Book a free discovery call or send a short brief — we will respond with sensible next steps.