Core service offering
Agents
We build agents that can understand a goal, gather context, use approved tools, and complete multi-step work while keeping humans in control of important decisions.
Quick answer
AI agents are software workflows that can take a goal, gather context, use approved tools, and complete multi-step work. Good business agents need guardrails: scoped permissions, approvals, logs, fallback paths, and clear limits on what they can do.
Built around your stack
LangChain
Framework for building and chaining multi-step LLM workflows.
Google ADK
Google's agent development kit for multi-agent orchestration.
OpenAI
Foundation models for reasoning, generation, and tool use.
Agents with bespoke tools and guardrails
We build the agent around the job it needs to complete: approved tools, retrieval, memory, evaluation, approvals, logs, and escalation paths. The stack can use LangChain, Google ADK, OpenAI, or our own models, but the important part is that every action is scoped to your workflow and risk profile.
What we build
- Research agents, operations agents, support agents, and internal assistant workflows.
- Tool integrations for CRMs, inboxes, knowledge bases, documents, databases, and task systems.
- Approval steps, audit trails, and boundaries so agents are useful without becoming risky.
What this helps with
- More work completed without adding more manual coordination.
- Consistent execution of repeatable knowledge-work processes.
- A practical agent layer that fits the way your team already operates.
Common questions
What is the difference between a chatbot and an AI agent?
A chatbot usually responds to a message. An AI agent can follow a goal across multiple steps, use tools, update systems, and check progress within defined limits.
How do you stop agents from taking risky actions?
We use scoped permissions, human approval gates, audit logs, test cases, fallback paths, and clear boundaries around which tools and data the agent can access.
Next step
Bring this into your business
If this maps to a bottleneck in your team, we can scope the smallest useful version, connect it to your current tools, and test it against real work before expanding it.
Talk to the team