AI Agents & Automation
Custom AI agents powered by LLMs that handle complex tasks and decision-making at scale. Grounded in your data, connected to your tools, and built with the guardrails production systems need.
AI agents go beyond a chatbot bolted onto your product — they reason about a goal, use tools, and take real action inside your systems. We design and build agents that are grounded in your own data, connected to the APIs and tools you already rely on, and constrained by guardrails that keep them predictable in production. Every engagement covers the full lifecycle: use-case discovery, prototyping, agent architecture and orchestration, integration, evaluation, and post-launch support — so you have one partner from proof of concept to a system you can trust in production.
AI Agents Built for Real Work
We match the right agent design to the problem you're actually trying to solve.
Conversational Agents
Chat and voice agents for customer support, sales, and onboarding — grounded in your data and able to hand off to a human when needed.
Autonomous Task Agents
Agents that plan, use tools, and execute multi-step workflows on their own — from research and data entry to end-to-end business processes.
AI-Augmented Internal Tools
Copilots embedded directly into your internal systems — surfacing answers, drafting content, and automating the busywork your team does daily.
Everything Your Agent Needs to Succeed
A complete, end-to-end AI agent development service — not just a prompt.
Agent Architecture & Orchestration
A well-structured agent design — planning, memory, and orchestration — so behavior stays predictable as complexity grows.
Custom LLM Integration
Integration with Claude, GPT, or open-source models, with prompt engineering and fine-tuning tuned to your use case.
Retrieval-Augmented Generation
Agents grounded in your own documents, databases, and knowledge base — accurate, up to date, and free of guesswork.
Tool Use & Integrations
Function calling and API connections that let agents take real action in your existing systems — CRMs, databases, internal tools, and more.
Multi-Agent Workflows
Coordinated teams of specialized agents that break complex processes into reliable, composable steps.
Guardrails & Safety
Output validation, hallucination mitigation, and human-approval gates for any action with real-world consequences.
Monitoring & Evaluation
Logging, tracing, and automated evals so you can measure agent quality and catch regressions before users do.
Human-in-the-Loop Controls
Review queues and escalation paths so a person stays in control of high-stakes or ambiguous decisions.
Post-Launch Support
Ongoing prompt and model updates, monitoring, and iteration as your data, tools, and use cases evolve.
Tools We Build With
From Proof of Concept to Production
Discovery & Use-Case Mapping
We identify the highest-value, lowest-risk tasks to automate and define clear success metrics before writing a line of code.
Prototype & Evaluate
A working prototype grounded in your real data, tested against representative scenarios to validate the approach early.
Agile Development
Two-week sprints building out orchestration, integrations, and guardrails, with continuous evaluation against real cases.
Deploy & Monitor
Production rollout with logging, evals, and alerting in place so agent quality is visible from day one.
A Partner Invested in Your Agent's Success
We don't just ship a prompt and disappear. Our team stays close to how your agent performs in the real world, evaluates it against real cases, and supports you well past launch day so it keeps improving as your business changes.
Common Questions
What's the difference between a chatbot and an AI agent?
A traditional chatbot follows scripted flows and answers questions. An AI agent reasons about a goal, decides what steps to take, calls tools or APIs to gather information or take action, and adapts as it goes — closer to a digital employee than a FAQ bot.
Which LLM do you use — GPT, Claude, or open source?
We're model-agnostic and choose based on your requirements around cost, latency, data privacy, and task complexity. Many of our builds use Claude or GPT-4, but we also work with open-source models when self-hosting or data residency is a priority.
How do you prevent the agent from hallucinating or making mistakes?
We ground agents in your actual data with retrieval-augmented generation, constrain their actions with tool schemas and validation, add human-approval gates for high-stakes decisions, and run automated evaluations against real scenarios before and after launch.
What happens after the agent is launched?
Every engagement includes a post-launch support window (see our Offers page for details), covering monitoring, prompt tuning, and bug fixes. We also offer ongoing retainers as your data, tools, and use cases evolve.
Ready to Build Your AI Agent?
Book a free discovery call and let's scope out the highest-value automation for your business.