How is this different from a generic chatbot?

A chatbot answers questions. An agent runs a workflow — fetches data, calls tools, decides between branches, escalates to humans when its confidence is low. We build the second one.

Can the agent touch our production systems?

Yes, with guardrails. We use scoped credentials, allowlisted actions, and explicit human approval for anything irreversible. See the Auto Issue Resolution case study for an end-to-end example.

Service pillar

AI Agents & Automation

When your business needs hands that don't sleep.

Lead-qualification agents, support agents, multi-step ops agents, and workflow automation. Production-grade systems that watch, decide, and act — with humans in the loop where it matters.

Book a 20-min scoping call →Try our AI on your problem ↑

What you get

Custom AI agents scoped to a specific business outcome — not generic chatbots
n8n / LangGraph / Anthropic Agents SDK orchestration for multi-step workflows
Voice and telephony agents via Vapi, Retell, or Twilio when conversation needs to happen on the phone
Full observability — every agent decision logged with reasoning, replayable, evaluatable
Human-in-loop checkpoints baked in by default. Your team owns the escalation logic.

When this is the right fit

You have a repetitive ops workflow that's eating senior time
Inbound volume is outrunning your team's bandwidth
You want to automate but not at the cost of brand or accuracy

Sample builds

Inbound lead qualification agent
Multi-channel (web, email, SMS, voice) qualification that engages every lead in under 60 seconds and books AEs only when they should be talking.
Customer-support resolution agent
Triage, reproduce, resolve — for everything from password resets to autonomous code-fix PRs through Claude Code.
24/7 ops monitor
Multi-agent system mirroring an org chart — production, maintenance, quality, inventory — coordinating through a shared event bus.

Tech we reach for

Anthropic Claude
LangGraph
Anthropic Agents SDK
n8n (self-hosted)
Vapi / Retell / Twilio
LangSmith / Langfuse
Postgres / Redis

Related case studies

FAQ

How is this different from a generic chatbot?
A chatbot answers questions. An agent runs a workflow — fetches data, calls tools, decides between branches, escalates to humans when its confidence is low. We build the second one.
Can the agent touch our production systems?
Yes, with guardrails. We use scoped credentials, allowlisted actions, and explicit human approval for anything irreversible. See the Auto Issue Resolution case study for an end-to-end example.