Assistants that are actually right
A demo chatbot takes an afternoon. A chatbot you can put in front of paying customers takes retrieval that finds the right document, guardrails that refuse gracefully, and evaluation that tells you when a change made things worse. That's the part we build.
Cited
answers traceable to a source
Eval-gated
no prompt ships untested
Portable
swap models without a rewrite
The usual starting point
What tends to be broken when clients call us
If two or three of these sound familiar, we've almost certainly fixed them before.
Confident, fluent, wrong answers reaching real customers
No way to measure whether a prompt change improved anything
Token costs that scale faster than revenue
Bots that can answer questions but can't complete an action
What we build
AI & Chatbots systems, end to end
Scoped to what your product actually needs — we don't sell modules you won't use.
RAG assistants
Document ingestion, chunking, hybrid search with reranking and citation-backed answers over your knowledge base, docs or ticket history.
Agentic workflows
Tool and function calling wired into your real systems — booking, refunds, ticket creation, CRM updates — with human approval where it matters.
Support deflection & handoff
Web, WhatsApp, Slack and in-app widgets, with clean escalation into Zendesk, Intercom or Freshdesk and full conversation context.
Evaluation & observability
Golden test sets, regression runs on every prompt change, hallucination and refusal tracking, per-conversation cost and latency dashboards.
Guardrails & safety
Prompt-injection defences, PII redaction, scope limiting, refusal behaviour and complete audit trails of what the model was shown.
Built to these standards
Compliance and accessibility requirements shape the architecture from the first sprint, so they never become a launch blocker.
- Prompt-injection hardening
- PII redaction
- GDPR
- Model-agnostic architecture
Typical stack
Boring, well-supported technology chosen for the next five years of your product — not for our CV.
FAQ
AI & Chatbots questions
Which model do you build on?
We keep the provider behind an interface and pick per workload — usually Claude for reasoning-heavy tasks and a smaller, cheaper model for classification and routing. You're never locked into one vendor's pricing.
Will our data be used to train a model?
No. We use enterprise API tiers with training disabled, and for sensitive deployments we can keep retrieval and storage entirely inside your own cloud account.
Building something in ai & chatbots?
Tell us where you are — an idea, a prototype, or a product that needs to scale. We'll give you a straight read on scope, timeline and cost.