FIELD GUIDE / AZION LABS
Choose an AI agent by the work it needs to do
Baseer organizes AI discovery for Arabic-speaking users through agent directories, model profiles, Saudi collections and supported Lab experiences. Start with a task you can describe and an output you can inspect.
By AZION LabsUpdated:
Who this is forArabic-speaking professionals, founders and teams comparing AI tools for concrete work.
A directory is a starting point
Baseer’s public directory organizes tools across 26 categories. A category narrows discovery, but a listing does not prove a product can complete your task. Read the provider description, supported inputs and expected output. Distinguish an underlying model from an agent that can coordinate tools or actions around that model.
Test the Arabic work you actually have
Use representative examples: a formal Arabic summary, a bilingual table or a Saudi-context question with a known source. Define an acceptable result before the trial. Review factual accuracy, language, formatting and handling of missing information separately. Keep the same examples when comparing candidates and record the model or product version.
Check the route from discovery to use
Catalog presence and Lab availability are different. Confirm where a candidate can be tried and which account, integration or payment is required. Before introducing work data, review the provider’s data handling and the permissions needed for the task. NIST’s AI framework offers context, measurement and risk-management concepts for this evaluation; it does not certify directory entries.
Workflow
A practical AI-tool selection process
- 01 →
Define
Write the task and acceptable output.
- 02 →
Shortlist
Filter by category, language and provider.
- 03 →
Try
Use the same representative inputs.
- 04 →
Review
Record quality, access and operating constraints.
Selection guidance, not a claim that every listed tool is available in Baseer Lab.
Decision guide
Four questions for an AI shortlist
| Dimension | Evidence to inspect | Decision question |
|---|---|---|
| Task fit | Supported workflow | Can it produce the needed output? |
| Arabic quality | Your Arabic test cases | Is meaning preserved? |
| Access | Trial and account requirements | Can your team use it? |
| Data handling | Provider policies and permissions | Is it suitable for this data? |
A comparison framework with no invented model scores or rankings.
Metrics explained
- Task completion
- Whether a result meets explicitly stated acceptance criteria.
- Latency
- Elapsed time to the output you need; define the start and end.
- Cost per completed task
- Total trial cost divided by accepted results, including retries.
- Coverage
- The tasks and languages actually included in an evaluation.
Questions, answered
Is every directory entry available in the Lab?
No. Check the separate supported Lab experience for each candidate.
Does a category indicate model quality?
It describes intended use. Quality requires a task-specific evaluation.
How do I compare Arabic performance?
Use the same Arabic examples and assess accuracy, language and formatting independently.
Where can I inspect an Arabic benchmark?
AZION’s AQWAL publishes its Saudi-context evaluation method, coverage and limitations.
References & further reading
- 01Baseer AI discovery directory ↗
Baseer
Official product directory; 26 categories observed on 23 October 2026.
- 02AI Risk Management Framework 1.0: Core ↗
NIST
Govern, Map, Measure and Manage are continuous functions, not a certification or sequential checklist.