AI Automation & Development

We build custom LLM applications, AI agents, RAG pipelines and workflow automation that eliminate repetitive work and open up capabilities that weren't possible before.

Practical, ROI-driven AI — integrated into your real tools and data, not science projects.

LLM applications and agents

We build model-agnostic systems: the app talks to an API or self-hosted model through one interface, so you can switch vendors or version models without a rewrite. Simple tasks route to cheap models; hard ones escalate.

• Agnostic stack: typical components are embeddings + vector search (RAG), rerankers, tool/function-calling and streaming UIs
• Agents follow a planning loop (ReAct-style) with explicit steps, tool access and a stop condition — never open-ended
• Latency budgets per task: chat first-token around or under a second, voice pipelines tested on real calls with stricter budgets

Guardrails, safety and data

AI mistakes are engineered against, not hoped away. Outbound actions pass approval gates, output is constrained by schema, and high-stakes or priced steps require a human.

• Prompt-injection resistant flows, PII redaction and scoped retrieval so sensitive data never reaches a model by default
• An evaluation harness with golden cases and graders runs before go-live and on every model change
• Audit logs per agent action so you can always see and explain what happened

Integration and ROI

Automation that floats is worthless; we wire agents into your CRM, calendar, telephony, email and internal tools via webhooks and connectors. The ROI assessment happens first and KPIs are agreed before build.

• Token and infra cost per completed task tracked against the value it creates
• Model upgrade path: when a better or cheaper model ships, we benchmark it against your cases
• Handover includes docs, costs dashboard and thresholds for scaling the workflow