AI service
Agents that plan, act and finish the job
We design multi-agent systems that don’t just answer questions — they plan, call tools, and complete real work on their own. From a single task-focused agent to orchestrated fleets with retrieval, long-term memory and safety guardrails, we build agents that hold up in production, not just in a demo.
01 / What changes for you
02 / Stack
The languages, frameworks and models we use to ship agentic ai systems — model-agnostic by design, each workload routed to the right model for quality, latency and cost.
Tech stack
Models we use
03 / Infrastructure
04 / Process
We map the workflow, the tools the agent needs, and what “done” looks like.
We wire up the agent loop, tools, retrieval and memory against your data.
A curated eval set gates every change — we ship on measured quality, not vibes.
We deploy to your cloud with monitoring, guardrails and cost controls.
05 / Good questions
A chatbot answers; an agent acts. Our agents plan multi-step tasks, call real tools and APIs, and complete work end to end — with guardrails and a human in the loop where it matters.
Every agent ships with an evaluation harness — a curated set of input/expected-output cases that runs on every change and gates releases. Plus tracing, cost limits and fallback paths.
We are model-agnostic and route per task — Claude for reasoning and orchestration, faster/cheaper models for high-volume steps, and self-hosted open-weights when privacy or cost demands it.
06 / More
Start
Tell us the problem — we’ll scope a pilot and ship something real. A senior engineer, not a sales rep, writes back.
Let’s manage or open the client Kanban
