AI development
LLM integration, knowledge assistants and document AI on your data.
- LLM APIs
- Python
- PyTorch
Services
AI agent development
An AI agent is software that can read a request, decide what to do, and take action in your tools: look up an order, update a CRM record, draft a reply, book a meeting.
We build agents for specific jobs, connected to your systems, with clear limits and a person in the loop wherever a mistake would be costly.
AI agents
What we build
Customer support agents
Answer questions, check orders, handle simple returns and escalate the rest, on WhatsApp, web chat or email.
Sales and lead agents
Qualify inbound leads, answer product questions and book meetings into your calendar.
Back-office agents
Read documents, enter data, reconcile records and prepare reports.
Internal knowledge agents
Answer your team's questions from policies, SOPs and past tickets.
Workflow agents
Multi-step processes across several tools, with approvals where required.
How our agents stay safe
Scoped permissions
An agent can only do what its job needs.
Confirmation first
Refunds, cancellations and payments need approval.
Human handover
Clear rules for passing to a person, with full context.
Full logs and evaluation
Every action is recorded, tested before launch and monitored after.
Architecture
How an agent fits into your business
Diagram: customer messages arrive from channels such as WhatsApp, web chat and email. An AI agent, made of a language model, tools and memory, and guardrails, reads each request and acts in your business systems such as the CRM, orders and calendar. Actions that need approval go to a person for review.
AI agent or chatbot?
A chatbot answers questions. An agent gets things done: it can call your systems (order database, CRM, calendar, email) to complete a task, then report back or hand over to a person. The difference is action, which is why guardrails matter.
Process
How we work
- Step 1
Pick the job
One well-defined task with clear success criteria.
- Step 2
Map the tools
Which systems the agent needs to read and write.
- Step 3
Build and test
Against real past conversations or tasks.
- Step 4
Supervised launch
People review agent actions for the first weeks.
- Step 5
Expand
More tasks and autonomy as performance is proven.
Technology
- LLM APIs
- Python
- Node.js
- WhatsApp Business Platform
- REST APIs
- Webhooks
Use cases
- Order-status and returns agent for an e-commerce brand on WhatsApp
- Appointment-booking agent for a clinic, synced with the doctor's calendar
- Lead-qualification agent for a real-estate developer
- Invoice follow-up agent for a finance team
FAQ
Frequently asked questions
What is the difference between an AI agent and a chatbot?
A chatbot answers; an agent acts. It uses your tools to complete tasks within limits you set, and hands over to a person when it should.
Can an agent work on WhatsApp?
Yes, through the WhatsApp Business Platform. The same agent can also serve web chat and email.
What if the agent gets something wrong?
Agents are designed for that: limited permissions, confirmation before important actions, human handover, and logs so issues are caught and fixed.
Which systems can it connect to?
Anything with an API, and many systems without one through integrations. We check yours during discovery.
How long does it take to build an agent?
A focused first agent is typically a matter of weeks, including a supervised launch period. We give you a plan after mapping the job and the tools.
Planning an AI agent?
Tell us what you're building. An engineer, not a salesperson, will reply within one business day with questions, an approach and next steps.