Custom AI Agent Development
Purpose-built AI agents that complete real work inside your operations.
What we deliver
We design and build custom AI agents that handle research, decisions, and actions across your tools, with guardrails, logging, and human review.
We build custom AI agents that take on the work your team does not have time for. Each agent is scoped to a specific job, connected to the systems it needs, and tested against examples from your real workflows. We start by mapping the task, the inputs, the decision points, and the outputs you expect. From there, we choose the right model, design the prompts and tool calls, and add memory and retrieval where it improves accuracy. We add guardrails, logging, and fallback paths so the agent fails safely and you can audit every run. We deliver the agent with clear documentation, an evaluation harness, and a plan for monitoring and iteration. The result is a focused agent that completes defined work end to end and gives your team time back for higher value tasks.
Built for teams like yours
Who it's for
- Operations leaders with repeatable knowledge work
- Founders scaling without adding headcount
- Product teams adding AI features
- RevOps and CS teams drowning in tickets
- Heads of data and analytics
Pain points we solve
- Manual research and triage taking hours per day
- Knowledge workers stuck on repetitive tasks
- Inconsistent quality across team outputs
- Slow turnaround on customer requests
- Tools that do not talk to each other
Capabilities
Everything we cover in this engagement.
- Agent scoping and task decomposition
- Prompt and tool design
- Retrieval and memory setup
- Function and API tool integration
- Guardrails and policy controls
- Evaluation harness and test suites
- Logging, tracing, and observability
- Deployment and handoff documentation
Our process
A clear, predictable path from kickoff to outcomes.
Discover
Map the task, inputs, outputs, and success criteria with stakeholders.
Design
Define agent scope, model choice, tools, and guardrails.
Build
Implement the agent, tools, retrieval, and evaluation harness.
Test
Run evaluations on real cases and tune prompts and tools.
Deploy
Ship to production with monitoring, logging, and a review cadence.
Deliverables & outcomes
What you get
- Working AI agent in your environment
- Source code and prompt library
- Tool and API integration layer
- Evaluation dataset and test reports
- Monitoring and logging dashboard
- Operating playbook and handoff docs
Outcomes you can expect
- Hours of manual work removed each week
- Consistent quality across runs
- Faster response on customer and internal requests
- Clear audit trail for every agent action
- A foundation to add more agents over time
What clients say
We had 14 cornerstone pages stuck on page two for 18 months. Their SEO crew rewrote the internal linking, cleaned up our schema, and shipped 22 supporting briefs over a quarter. Eight of those pages broke top three by month five. Organic pipeline went from a trickle to our second-largest source. Felt like watching interest compound.
We had been prototyping an AI quoting agent for nine months and could not get it past demo quality. They came in, scoped a real eval set, swapped our retrieval layer, and added guardrails for the edge cases that kept burning us. Went live in seven weeks. It now handles 41 percent of inbound quote requests without a human touching them.
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ExploreFrequently asked questions
Quick answers to the questions we hear most.
How is a custom agent different from a chatbot?
Which models do you use?
Can the agent run on our infrastructure?
How do you prevent the agent from making mistakes?
What happens after launch?
Ready to put an AI agent on a real job?
We scope the work, build the agent, and ship it with the guardrails your team needs.