We build agents that do real work — plan, call tools, read and write to your systems, and hand off to a human when the stakes are high.
Not a menu of buzzwords — the concrete things our team delivers on every agentic ai engagement.
LangGraph or CrewAI topologies designed for your workflow — planner, executor, critic, not a single monolith.
Typed tool schemas, allowlists, and dry-run modes so agents never call production APIs they should not.
Short-term scratchpads, long-term vector memory, and structured state with replay — debugging agents made real.
Approve, edit, or reject steps before agents touch anything irreversible. Configurable per workflow.
Every agent run traced in LangSmith or Langfuse with per-step cost, latency, and success metrics.
Agents call your APIs, databases, CRMs, and browsers — via MCP, function calling, or custom tool adapters.
No discovery phase that never ends. Each step has a deliverable, a date, and a demo.
We pick a single high-value workflow and map every decision, tool, and handoff before writing a line of agent code.
Topology chosen (single-agent, planner-executor, or multi-agent), tools typed, and eval set built from real runs.
Agents run alongside humans, proposing actions without executing. We tune until acceptance rate clears the bar.
Go-live with human checkpoints on irreversible actions. Graduate steps to full autonomy as eval data accumulates.
Opinionated defaults — not a buzzword bingo card. We swap pieces when your product calls for it.
A 30-minute call. We'll talk scope, timelines, and what a realistic first release looks like. NDA signed before we start.