Automate & Innovate with AI-Powered Solutions
From customer-facing AI features to back-office automation that runs while you sleep. We turn LLMs and APIs into shippable product.
What we mean by AI Automation
Two flavours: customer-facing AI features (chatbots, summarisation, recommendations, RAG over your knowledge base) and back-office automation (workflows, data pipelines, internal copilots). We pick the right model for the job, keep latency reasonable, and never let a hallucination touch a customer.
AI Automation projects we deliver
RAG-powered chatbots and assistants
Grounded in your own docs, knowledge base, or product data. With proper citations and refusal handling.
Workflow automations (n8n, Zapier, custom)
Connect your CRM, mailbox, Stripe, Notion, and more. Eliminate the spreadsheet jobs.
Smart features inside your app
Auto-tagging, summarisation, transcription, sentiment, image generation — embedded where users actually need them.
AI-augmented internal tools
Copilots for ops, sales, support — fed your real data, with the guardrails that keep them honest.
How we approach a project
Find the boring work first
We audit your team's repeatable tasks before reaching for any model. Often the win is plumbing, not AI.
Pick the model and stack
OpenAI, Anthropic, open-source — picked per task on cost, latency, privacy, and quality. No religion.
Prototype, evaluate, harden
Build, write evaluations, measure regressions, then wire into your product or workflow.
Add guardrails and observability
Rate limits, prompt-injection defences, cost dashboards, and human-in-the-loop where stakes are high.
What we use
- OpenAI
- Anthropic Claude
- LangChain
- n8n
- Pinecone
- Supabase pgvector
- Vercel AI SDK
- Zapier
Why pick us for AI Automation
Production AI, not demo-ware
We build AI features that survive contact with real users — with evals, fallbacks, and cost ceilings.
We say no to bad fits
If a problem doesn't need AI, we say so. You'll get a cheaper, more reliable answer.
Privacy-aware by default
PII handling, prompt logging policy, and on-prem options when your data can't leave the building.
Real projects, real metrics
Browse the portfolio for case studies — including ones built with this exact stack.
Common questions
Will the AI hallucinate or leak prompts?
Both can happen — and we engineer specifically against them. Retrieval grounding, output validation, system-prompt isolation, and red-team tests are part of every project.
How much does this cost to run?
We give you a per-task cost estimate before building, based on token volumes and the model tier. Then we set hard cost ceilings per user / per day.
Can you use my private data without sending it to OpenAI?
Yes — Anthropic and OpenAI both offer enterprise / no-train tiers, and for highly sensitive cases we can self-host open-source models.
Can you build AI agents that take actions?
Yes — with appropriate human-in-the-loop and reversibility. Agents that can spend money or send emails always go through approval.
How do you measure AI quality?
Per-feature evals — synthetic test sets, human spot-checks, and production sampling. Quality gets graded continuously, not once at launch.
Ready to Build Your Dream App?
Let's discuss your project in a free 30-minute discovery call. No commitment required.