AI Agents
Autonomous systems that work while you sleep.
We design and deploy custom AI agents that replace entire workflows — not chatbots dressed up with a fancy UI. Multi-agent orchestration, RAG pipelines, decision engines, and autonomous process handlers built for production at scale.
Operations & logistics
Route planning, load balancing, and exception handling — autonomously, at enterprise scale.
Customer support
AI agents that resolve tickets, escalate edge cases, and write better responses than most humans.
Document & data processing
Extract, classify, and act on unstructured data from PDFs, emails, and forms.
Sales qualification
Inbound lead scoring, research, and outreach — running 24/7 without an SDR team.
Decision & workflow mapping
We embed with your team for 1–2 weeks to document every decision type, the data it requires, the business rules applied, and the edge cases humans currently handle. We identify what can be fully automated vs. what needs a human-in-the-loop.
Agent architecture design
We design a multi-agent system with clear specialisation — routing agents, specialist sub-agents, and a supervisor that escalates when confidence drops. Every agent gets a defined tool set, structured memory, and deterministic fallback logic.
Build & integration
We build each agent with typed tool calls, full audit logging, and integration into your existing stack — CRM, ERP, SaaS tools — via API middleware. No black boxes, no vendor lock-in.
Eval, shadow mode & handoff
We run the system in shadow mode, comparing agent decisions with human decisions, tuning until accuracy exceeds your threshold. Phased rollout with monitoring dashboard. You see every decision, every escalation, in real time.
- ↗Custom LLM prompt engineering & fine-tuning
- ↗Multi-agent orchestration (LangGraph, CrewAI)
- ↗RAG pipelines with vector databases
- ↗Agent monitoring & evaluation dashboards
- ↗Real-time inference APIs
- ↗Human-in-the-loop escalation flows
What's the difference between an AI agent and a chatbot?
A chatbot responds to messages. An AI agent takes actions — calling APIs, updating records, making decisions, and completing multi-step tasks without a human in the loop. Agents are evaluated on outcomes, not conversations.
How long does it take to build an AI agent?
Most production agents take 8–16 weeks from kickoff to live. Simpler automation workflows can be done in 4–6 weeks. Timeline depends on the complexity of your decision logic and the state of your existing data infrastructure.
Can AI agents replace human employees?
For repetitive, rule-based decisions — yes, often entirely. For judgement-heavy or relationship-sensitive work, agents handle the volume while humans focus on the genuinely hard cases. Most clients see a reduction in headcount over 12–18 months.
What if the agent makes a wrong decision?
We build confidence thresholds and escalation paths into every agent from day one. When an agent isn't sure, it routes to a human rather than guessing. All decisions are logged with full reasoning for audit.
