AI Agent Development Services
AI that doesn’t just answer - it gets work done.
Custom, domain-specific AI agents that plan, use your tools, and execute multi-step business tasks - with the observability and guardrails production demands.
A chatbot responds. An agent acts: it reasons about a goal, checks its work, and completes the task.
We build agents tailored to a specific job in your business - triaging tickets, processing documents, researching and drafting, updating records across systems. They combine reasoning, tool use, memory and retrieval to handle work that used to need a person at a keyboard.
Because autonomy without control is a liability, we engineer for production: clear task boundaries, human-in-the-loop approval on risky actions, full tracing of every step, and hard limits that stop runaway behaviour and cost.
What we build
Agents built for real workflows
Scoped to a job, connected to your tools, and safe to run in production.
Tool & API use
Agents that call your internal APIs, databases and SaaS tools to actually complete tasks, not just talk about them.
Planning & reasoning
Multi-step task decomposition with the ability to adapt when a step fails or new information appears.
Memory & context
Short- and long-term memory so agents maintain context across a task and across sessions.
Human-in-the-loop
Approval gates on sensitive or irreversible actions, keeping a person in control where it matters.
Observability
Full tracing of prompts, tool calls and decisions for debugging, audit and continuous improvement.
Guardrails & limits
Termination caps, permissions and validation that prevent runaway loops, unsafe actions and cost blowups.
How we deliver
A path from idea to production
A pragmatic engagement model that de-risks adoption and gets a working system in front of your users fast.
- 01
Workflow mapping
We pick a high-value, well-bounded task and map the steps, tools and decisions it involves today.
- 02
Agent design
We design the reasoning loop, tools, memory and guardrails - and where humans stay in the loop.
- 03
Build & evaluate
We implement the agent and test it against real scenarios, tracing every run to catch failure modes.
- 04
Deploy & improve
We ship with monitoring, then expand scope and autonomy as trust and accuracy are proven.
Tools & stack
Technologies we work with
We stay model- and vendor-flexible, choosing the stack that fits your data, budget, and compliance needs.
- LangGraph
- Anthropic Claude Agent SDK
- OpenAI Agents SDK
- CrewAI
- LlamaIndex
- Pydantic AI
- MCP
- Vector databases
- Python / TypeScript
- LangSmith / tracing
Where it fits
Use cases & industries
For repetitive, multi-step knowledge work that follows rules but needs judgement.
Support automation
Triage, research and resolve or escalate tickets across your systems.
Document processing
Read, classify, extract and route documents end to end.
Research & drafting
Gather information and produce first-draft reports, briefs or replies.
Data operations
Reconcile, enrich and update records across CRMs and databases.
Onboarding & IT
Provision access and handle routine internal requests.
Sales ops
Prepare call notes, update CRM and follow up automatically.
Common questions
A chatbot generates text. An agent pursues a goal - it plans, uses tools to take real actions in your systems, observes results and adjusts until the task is done.
We scope each agent tightly, require human approval on risky actions, enforce permissions and hard limits, and trace every step so nothing runs unchecked.
No. Agents connect to your current stack through APIs and MCP, automating work across the tools you already use.
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