Defined roles
Each agent has one job: researcher, analyst, writer, checker or operator. Clear roles make results easier to test and to trust.
Research. Analysis. Execution.
Agent teams that work like your best department
Specialist AI agents research, analyse and execute together, each with a defined role, tools and knowledge. Your people stay in charge, with approval gates wherever decisions matter.
Sound familiar?
Skilled people spend their days gathering, copying and reformatting information.
01
A single chatbot can’t follow a multi-step process across several systems.
02
You want automation, but not an AI that acts without anyone checking its work.
03
What we build
Capabilities
Tools, knowledge and memory
Each agent gets only what its role needs: your documents, your systems through scoped access and a memory of past decisions.
Hand-offs between agents
Work moves from agent to agent like a well-run team, with context passed along and every step recorded.
Human approval gates
You decide where a person must approve before anything is sent, published or changed. Agents prepare; your people decide.
Evaluation before go-live
We test quality, cost and failure modes on real cases before launch. You choose the AI provider: OpenAI, Anthropic, Google Gemini or open-weight models.
Illustrative scenario
A bilingual board briefing, researched by agents
A fictional investment team in the Gulf needs a weekly sector briefing in Arabic and English, drawn from reports, news and internal notes.
- 01
A research agent collects approved sources and internal notes on the sector.
- 02
An analyst agent extracts the key figures and flags conflicting information.
- 03
A writer agent drafts the briefing in Arabic and English, with sources cited.
- 04
A checker agent verifies every claim against its source and marks anything uncertain.
- 05
An analyst reviews, edits and approves the briefing before it reaches the board.
You receive
- Agent team design: roles, tools, hand-offs and approval points
- A working agent team connected to your knowledge and systems
- Evaluation set and report covering quality, cost and failure modes
- Audit trail of every agent action and human decision
- Runbook and handover for your team
What we measure together
- Time from request to approved output
- Share approved without edits
- Cost per task
- Errors caught at review, by type
Measures and baselines are agreed with you before work starts. We do not promise numbers in advance.
How an engagement runs
- 01
Map the work
We break the workflow into tasks and decide which belong to agents and which stay with people.
- 02
Design the team
Roles, tools, knowledge sources, hand-offs and approval gates, all agreed with you.
- 03
Build and evaluate
We build the agents and test them on real cases for quality, cost and failure modes.
- 04
Go live with oversight
We launch with approval gates in place, then tune the team based on what your reviewers see.
Questions
Straight answers.
Which AI models do you use?
The one that fits your task, policy and budget. We work with OpenAI, Anthropic, Google Gemini and open-weight models, and design the system so the provider can be changed later.
Can agents act without human approval?
Only where you decide they can. You set the approval gates: low-risk steps can run automatically, while anything sensitive waits for a person.
Do the agents work in Arabic?
Yes. Today’s models handle Modern Standard Arabic well, while dialects and specialist terms vary more by task and provider. That is why we evaluate on your own Arabic samples before go-live.
Who owns the agents we build together?
You do. The instructions, configuration, code and evaluation sets are yours, and so is your data.
Related solutions
AI command centres
A shared workspace to assign tasks to agents, follow them live and approve results, with a full audit trail.
ExploreSystems integration
Connect AI to your CRM, ERP, documents, email and messaging, with scoped access and human review.
ExploreAI strategy & pilots
Map your workflows, prioritise use cases and prove one in a focused pilot with real data.
ExploreLet’s talk
Start with one workflow.
Tell us about a process that slows your team down. In a 45-minute discovery session we show what an agent team could do with it, and what it would take.