✦Service
AI agents that do the work.
An AI agent goes beyond answering questions: it reads a request, works out the steps, and takes actions in the tools your team already uses. We build agents with narrow, well-defined jobs, clear permissions and human approval on anything that matters, so they save real hours without becoming a black box.
01What we build
What you get.
- 01
Task-specific agents
Agents for one job done well — such as updating CRM records from emails, preparing quotes or reconciling orders — rather than a vague do-everything bot.
- 02
Tool integrations
Secure connections to your CRM, ERP, ticketing, email, calendars and spreadsheets, with each tool's permissions scoped to the task.
- 03
Approval steps
Human-in-the-loop checkpoints in Slack, Teams, WhatsApp or email so a person confirms payments, customer messages or record changes.
- 04
Multi-step workflows
Agents that plan and carry out several steps, recover from errors and stop safely when something looks wrong.
- 05
Audit trail and monitoring
A log of every decision, tool call and approval, plus alerts when the agent fails or behaves unexpectedly.
02Use cases
Where it pays back.
- 01
Sales operations
Read inbound enquiries, enrich the lead, create the CRM record and draft a tailored first reply for a salesperson to send.
- 02
Finance teams
Match invoices to purchase orders, chase missing documents and prepare entries for an accountant to approve.
- 03
Customer support
Triage tickets, gather order and account details, and propose a resolution the support agent can accept or edit.
- 04
Logistics
Watch shipment updates, flag delays, notify customers and open tasks for the operations team.
- 05
Recruitment
Screen applications against agreed criteria, schedule interviews and keep candidates updated — with final decisions left to people.
03Process
How we build it.
- 1
Choose one job
We pick a repetitive, rules-heavy task with a clear definition of done and measure how it is handled today.
- 2
Design guardrails
We agree which actions the agent may take alone, which need approval, and what it must never do.
- 3
Build and dry-run
The agent runs in 'suggest only' mode on real cases so your team can compare its choices with their own.
- 4
Switch on and monitor
We enable actions step by step, watch the logs and extend the agent's scope only when it has earned it.
Typical stack
- OpenAI / Claude / Gemini APIs
- LangGraph / LangChain
- Python / FastAPI
- n8n
- Postgres
- Redis queues
- Slack / Teams APIs
- AWS / Azure / GCP
04Where we work
Teams we work with.
- Dubai & UAEAI chatbots, agents and automation for businesses in Dubai and the UAE — Arabic and English assistants, WhatsApp-first, delivered remotely in your working day.
- Europe & UKAI agents, RAG search and automation for UK and EU companies — privacy-first design with GDPR and the EU AI Act in mind, EU data residency, many languages.
- USAAI agents, copilots and apps for US startups and enterprises — security-minded engineering, HIPAA-aware design and async delivery across US time zones.
- IndiaAI chatbots, document automation and apps for Indian businesses — GST-ready invoice processing, Indian-language WhatsApp bots and DPDP-aware design.
05FAQ
Common questions.
ask us anything else →
01How is an AI agent different from a chatbot?
A chatbot mainly answers questions. An agent is given tools — such as your CRM, email or database — and can take actions with them, for example creating a record or sending a draft for approval. That extra power is why we design agents with tight permissions, approvals and logging.
02Is it safe to let AI take actions?
It can be, when the scope is narrow and the controls are clear. We start agents in suggest-only mode, require human approval for sensitive actions, limit each integration to the minimum permissions and keep a full audit log. Actions are switched on gradually as the agent proves reliable.
03Which tools can an agent work with?
Anything with a usable API, and some tools through automation platforms. Typical examples are HubSpot, Salesforce, Zoho, Odoo, SAP Business One, Google Workspace, Microsoft 365, Slack, Teams, WhatsApp and internal databases. We check access and rate limits early in the project.
04What happens when the agent gets something wrong?
Errors are expected and planned for. The agent stops and asks for help when it is unsure, every step is logged so the cause can be traced, and fixes are tested against past cases before release. For important actions a person approves before anything changes.
05Do we need a large AI budget to start?
No. We recommend starting with one well-defined task and a short pilot on real data. That shows whether the agent saves time before you invest further. Costs depend on scope and model usage, which we estimate with you after an initial conversation.
06More services
Other things we build.
- AI chatbots & voice assistantsanswers from your docs
- Document intelligenceexceptions go to a human
- Workflow automationboring work, automated
- Knowledge search (RAG)every answer cites a source
- Computer visiontrained on your images
- Data analytics & forecastingwhy did this drop?
- AI web & mobile appswe run our own product
Have a process worth automating?
Tell us about it — we'll reply with how ai agents could handle it, what data it needs and a rough plan. The first conversation is free.