Meet your future AI workforce.
Each AI Employee is purpose-built for one department, connects to your existing tools, and operates autonomously — from triaging support tickets to reconciling financial reports.
Try a real AI Employee, right on this page.
What businesses have us build for.
Lead Qualification & CRM Upkeep
Agents that engage inbound leads, score them against your ICP, update CRM records, and hand off warm conversations to your closers — no manual data entry.
Data Extraction & Reporting
Pull structured data from documents, emails, and spreadsheets. Generate reports, summaries, and dashboards on demand without waiting on a data team.
Always-On Customer Support
Handle tier-1 tickets around the clock. Answer from your knowledge base, triage by urgency, and escalate only when a human touch is required.
Content & Workflow Automation
Draft proposals, generate invoices, schedule meetings, and route approvals — agents that own the workflow from trigger to completion.
How we build and deploy each agent.
Every AI Employee follows the same four-phase lifecycle — from understanding your workflows to ongoing operation and improvement.
Discovery & analysis
We audit how the department actually works — tools, handoffs, decision points — and rank where an agent has the biggest lever. Your processes, not a generic template.
Architecture
We design the agent system: which data it reads, which tools it can act in, where it escalates to a human, and how success gets measured.
Build & training
We build the agents and train them on your data, processes and language. Every action is traceable, so you can see exactly what the agent did and why.
Operate & improve
We run the agents and keep developing them. Agent-as-a-service — not a one-off project handover with a manual attached.
Agents for your department.
Browse by department or explore all six AI Employees below.
Dive deeper.
Articles, guides, and explainers to help you understand how autonomous department agents work and what they can do for your business.
What Is an AI Employee?
Unlike a chatbot that answers questions, an AI Employee is a persistent autonomous agent that takes action across your tools — creating tickets, updating records, generating reports, and more.
How We Build Agents
Each agent is purpose-built for one department using a modular architecture: perception layer, reasoning engine, tool integrations, and an escalation gate to human reviewers.
Data Security & Compliance
Agents operate in dedicated virtual private clouds with encryption at rest and in transit. We never train base models on your data, and you control retention policies.
Costs & ROI
Pricing is per-agent per-month with volume discounts. Most clients see a positive return within the first quarter from reduced staffing costs and faster throughput.
AI Employee vs. Chatbot
A chatbot waits for questions. An AI Employee owns outcomes — it monitors systems, initiates actions, escalates intelligently, and improves from feedback without retraining from scratch.
Glossary of Terms
From retrieval-augmented generation (RAG) and tool-calling to escalation gates and confidence thresholds — plain-English definitions of the concepts behind autonomous agents.
Build vs. Buy
Building an in-house AI agent means hiring ML engineers, maintaining infrastructure, and iterating for months. Our agents deploy in weeks and improve continuously.
Understanding ROI
Estimating savings from department automation: hours reclaimed, reduced escalation volume, faster response times, and fewer errors — all measurable from week one.
Are You Ready for an AI Employee?
The best candidates have documented workflows, structured data sources, repetitive but rule-based tasks, and a clear handoff point where human judgment is required.
First cases.
We publish case studies only with client approval. Here is one anonymized example of the work we do.
Financial services compliance (anonymized)
A financial advisory firm deployed our Document and Research agents to automate regulatory filing reviews and competitor monitoring. The agents now process 200+ documents per week and surface compliance risks in hours instead of days.
This is an illustrative example based on a client engagement. The client identity and specific figures have been anonymized.
More case studies coming soon
We publish detailed case studies only after receiving client approval. If you'd like to be featured, we'd love to hear from you.