AI integrations, agents & chatbots for US, UK & EU
We ship AI features that actually work in production
AI integrations, AI agents, AI chatbots, RAG systems, and LLM-powered product features. Production-grade — with eval suites, cost guardrails, prompt versioning, and observability. We work with Claude (Anthropic), GPT (OpenAI), Gemini (Google), and open-source models. Typical engagements run 6-20 weeks.
- ✓ AI integrations into existing SaaS, web, mobile, or desktop apps
- ✓ AI agents (multi-step, tool-using, with proper guardrails)
- ✓ AI chatbots with retrieval-augmented generation (RAG)
- ✓ LLM-powered product features (search, copilots, summarization)
- ✓ Eval suites + cost monitoring + prompt versioning from day 1
What you get
AI integrations
Add LLM features to your existing product — content generation, search, summarization, classification, extraction. Real production patterns with caching and rate limiting.
AI agents (multi-step)
Tool-using agents with planning, retries, observability, and human-in-the-loop checkpoints. Built on Claude, GPT, or Gemini with proper guardrails.
AI chatbots & RAG
Retrieval-augmented chatbots over your own docs/data. Vector DBs (pgvector, Pinecone, Qdrant), reranking, hybrid search, citations. Not toy demos.
Eval-first engineering
Every prompt comes with an eval suite. We measure quality regressions before deploy. No 'works on my machine' AI features in prod.
Cost guardrails
Per-user budgets, model routing (Haiku for cheap, Sonnet/Opus for hard), prompt caching, batch APIs. AI bills don't surprise you.
Provider-agnostic
We use Claude, GPT, and Gemini. We can swap providers without rewriting your app — important when one provider has an outage or price hike.
How we work
Discovery + eval design (2 weeks)
Define the AI feature, draft eval criteria, pick the right model, scope cost and latency budgets.
Build (4-16 weeks)
Iterative builds with eval-driven development. Weekly demos with real eval scores, not vibes.
Ship + monitor
Production deploy with prompt versioning, cost dashboards, drift detection, and incident response runbook.
Frequently asked
How much does AI integration cost?+
Pricing depends on scope — single integration vs full agent system, RAG complexity, eval requirements, and ongoing inference costs. We give you a fixed proposal after a 2-week discovery sprint. Book a discovery call for a precise quote.
Which models do you work with?+
Claude (Anthropic), GPT (OpenAI), Gemini (Google), and open-source models via Together/Replicate/Groq. We pick based on your cost/latency/quality requirements — not provider loyalty.
Do you build voice agents?+
Yes — using Deepgram, Cartesia, ElevenLabs, and OpenAI Realtime API. Phone-based voice agents are a separate engagement type — book a call for scoping.
Can you integrate AI into our existing app?+
Yes — that's most of our AI work. We add LLM features (search, copilots, summarization, generation) to existing SaaS or web apps without rewriting your stack.
How do you handle hallucinations?+
RAG with citations, structured output (JSON schema or function calling), confidence scoring, output validation, human-in-the-loop checkpoints for high-stakes flows. We design the architecture to fail safely.
What about data privacy?+
We use providers with enterprise data agreements (Anthropic, OpenAI, Google). Customer data is not used for training. Optional: self-hosted open-source models via vLLM or Ollama for sensitive use cases.
Ready to start?
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