AI Agents That Do Things

Not chatbots. Not question-answering systems. Autonomous agents that execute workflows — updating CRM records, processing invoices, responding to support tickets, triggering business processes.

Repetitive workflows consume your team's time

Data entry, ticket routing, invoice processing, status updates. Work that needs to happen but doesn't need human judgment.

Off-the-shelf automation tools are too rigid

zapier and similar tools handle simple if this then that logic. Real workflows have branching paths, exceptions, and conditional decisions.

You've tried building agents but they're unreliable

lLM based agents are powerful but unpredictable. Without proper guardrails, they make mistakes that damage trust with your team.

Scaling manual processes doesn't scale your team

Adding headcount to handle repetitive work isn't sustainable. You need automation that learns and adapts.

Most AI agent implementations are wrappers around an LLM call with a system prompt. They work beautifully in the demo. In production, the agent hallucinates, takes wrong actions, or gets stuck in loops.

The other extreme is rigid RPA (robotic process automation). These systems work reliably but break the moment anything changes — a button moves, a field is renamed, a process is updated.

Both approaches miss the middle ground: agents that are flexible enough to handle variation but constrained enough to be reliable.

We build agents with three layers: reasoning, action, and guardrails. The reasoning layer decides what to do. The action layer executes it. The guardrails layer prevents the agent from doing things it shouldn't.

Agents integrate with your existing tools through APIs and webhooks. They can read and write to your CRM, ticketing system, database, and communication tools. When they encounter something they can't handle, they create a handoff task for a human.

We include human in the loop workflows for high stakes actions. The agent suggests an action, a human approves it, the agent executes it. This builds trust gradually. As the agent proves reliable, you can increase its autonomy.

Multi-Step Workflow Execution

Agents execute complex workflows with branching logic, conditionals, and exception handling.

Tool Integration

Connect to Slack, Salesforce, HubSpot, Jira, Zendesk, and any API. Agents read and write data in your existing tools.

Human-in-the-Loop

Configurable approval workflows. Agents handle routine tasks and escalate uncertain situations to humans.

Monitoring & Audit Logs

Every action is logged. You can review what the agent did, why it did it, and override any decision.

Fallback & Recovery

When an agent encounters an error, it retries, escalates, or follows a recovery procedure. It doesn't just fail silently.

Performance Analytics

Track resolution rates, handling times, and escalation patterns. Continuously improve agent performance.

Workflow Audit

We map your existing workflows, identify automation opportunities, and document decision points and exceptions.

Agent Design

Design the agent architecture: tools, guardrails, escalation paths, and human in the loop workflows.

Build & Test

Build the agent with your data. Test against historical scenarios. Iterate on edge cases.

Deploy & Monitor

Deploy with human supervision. Monitor performance. Gradually increase autonomy as the agent proves reliable.

Production reliability

Our agents have guardrails, fallbacks, and monitoring. They don't just work in demos.

Tool integration expertise

We've integrated agents with dozens of business tools. You don't need to build custom connectors.

Safety-first approach

We start with tight guardrails and expand as the agent proves reliable. Your business processes are protected.

Measurable results

We track time saved, error rates, and escalation patterns. You know exactly what value the agent is delivering.