Autonomous AI agents that actually do the work
Agentic solutions are AI agents that plan, use tools, remember context, and act toward a goal on their own. We build them with the same engineering discipline we apply to any production system, so reasoning, memory, and orchestration hold up under real load.
30-minute call · no pitch deck · no obligation
Everything this capability ships
Senior-owned, AI-accelerated, and wired into your stack. Not a deck of recommendations.
Autonomous agents
Agents that understand a goal, plan, act, and iterate. Built on the frameworks your team can maintain after we hand over.
Multi-agent orchestration
Manager, worker, and critic patterns. Clear contracts between agents so behaviour is predictable under load.
Tool use and function calling
Safe, typed interfaces to your APIs, databases, and internal services. Agents use tools the way your team does.
Memory systems
Short-term scratchpads, long-term vector stores, and structured state. Memory tuned for the task, not generic.
Guardrails and approvals
Human-in-the-loop on critical paths, hard policy limits, and structured outputs. Safety as code, not a post-hoc review.
Evaluation and observability
Trace every step, replay every decision, measure every run. Fix regressions before users see them.

An autonomous support agent that resolves half of every queue
Atlas Support · B2B SaaS
We designed and shipped a multi-agent support system, with tool-use, memory, and an evaluation harness, wired into their helpdesk and internal APIs. It triages, drafts, and resolves routine tickets end-to-end, and escalates cleanly the moment confidence drops.
From first call to production
Task analysis
Map the workflow the agent will replace or assist. Define success criteria, failure cost, and where a human stays in the loop.
Agent design
Pick the smallest viable architecture. Single agent beats multi-agent unless the task demands it.
Tool and memory wiring
Build typed tools against your systems. Design memory for what the agent actually needs to remember.
Evaluation harness
Golden set, adversarial set, live traffic replay. Ship with the ability to catch regressions the moment they happen.
Production rollout
Gradual rollout, observability wired up, rollback rehearsed. The pod that built it operates it.
What it actually solves
Customer operations
Triage, classify, draft replies, and escalate with full audit trails. Agents that free humans for judgement work.
Research and analysis
Gather, synthesise, and cite across internal and external sources. Deterministic output formats your team can trust.
Process automation
Multi-step workflows across tools. Agents that replace brittle scripts with traceable, improvable reasoning.
Developer assistants
Internal agents wired into your codebase, docs, and tickets. Fast answers with the context your team actually has.
Tools we reach for
Agent frameworks
- LangGraph
- OpenAI Agents
- Anthropic SDK
- DSPy
- Mastra
Vector stores
- pgvector
- Pinecone
- Weaviate
- Qdrant
- Turbopuffer
Orchestration
- Temporal
- Inngest
- Trigger.dev
- AWS Step Functions
Observability
- LangSmith
- Helicone
- OpenTelemetry
- Grafana
Questions, answered
Structured outputs, hard policy limits, and human-in-the-loop checkpoints on high-impact actions. Safety is designed in, not bolted on.
OpenAI, Anthropic, Google, Mistral, and open-weight models on your own infrastructure. We pick for the task, not the logo.
Yes. Agents are deployed to your cloud and your infrastructure. We do not lock you into ours.
Golden sets for known behaviour, adversarial sets for edge cases, and live traffic replay for regression detection. Every run is logged.
Sometimes. Usually they glue tools together and take the routine work off humans so your team gets leverage without a migration.
Let’s build it together.
One senior team, one flat monthly subscription, no lock-in. Book a call and we’ll map the fastest path to shipped.