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Atlas of AI

Specialized models for every business job, ranked and ready to build.

Find AI worth owning

580 Specialist Models, one per business decision.

42 of 580 models

#22 overall · #6 in Software

Code Planning

Given a coding task or request, what is the multi-step plan (files to touch, order of edits, subtasks) before any code is written?

Owned by VP Engineering, Head of Developer Productivity

Software
Build it: Code PlanningRead the guide: Code Planning

#34 overall · #7 in Financial services · #10 in Healthcare

Regulatory Submission

Is this regulatory submission package complete, internally consistent, and ready to file with the relevant authority?

Owned by VP Regulatory Affairs, Chief Compliance Officer

Financial services
Build it: Regulatory SubmissionRead the guide: Regulatory Submission

#38 overall · #5 in Banking · #10 in Financial services

SAR Narrative

Does the activity warrant a suspicious activity report, and how should the narrative be documented?

Owned by BSA/AML Officer, Head of Financial Crime

Banking
Build it: SAR NarrativeRead the guide: SAR Narrative

#48 overall · #5 in Insurance

Appeals Generation

Can this denied claim be appealed, and what appeal letter and evidence package gives it the best chance of being overturned?

Owned by VP Revenue Cycle Management, Director of Denials Management

Healthcare
Build it: Appeals GenerationRead the guide: Appeals Generation

#51 overall · #1 in Retail

Board Narrative

What narrative commentary and talking points should accompany this quarter's board materials given the underlying financial and operational results?

Owned by Chief Financial Officer, VP Financial Planning & Analysis

Financial services
Build it: Board NarrativeRead the guide: Board Narrative

#73 overall · #2 in Cross-industry

Documentation Generation

What technical documentation (API reference, code comments, README, runbook) should be generated or updated for this codebase change, and is it accurate enough to publish?

Owned by VP Engineering, Head of Developer Experience

Cross-industry
Build it: Documentation GenerationRead the guide: Documentation Generation

#105 overall

Test Repair

Given a failing test, what is the minimal correct fix, to the code or to the test, that makes it pass without masking a real regression?

Owned by VP Engineering, Head of Developer Productivity

Software
Build it: Test RepairRead the guide: Test Repair

#172 overall · #10 in Cross-industry

Competitive Messaging

Given a specific competitor and deal context, what positioning, proof points, and objection-handling language should a rep or marketer use right now?

Owned by VP Product Marketing, Head of Competitive Intelligence

Cross-industry
Build it: Competitive MessagingRead the guide: Competitive Messaging

Choose a model you can own.

Model leaderboards are a starting point. The decision is your task, your output contract, your hardware, and your right to deploy. This directory turns that into a short list you can test.

  • Qwen

    Alibaba Cloud · China
    Qwen is Alibaba Cloud’s open-weight model family. It spans small models that are practical to fine-tune through larger mixture-of-experts releases.
    Active in Oumi

    Profile: Qwen

  • DeepSeek

    DeepSeek · China
    DeepSeek publishes open-weight language models, including large mixture-of-experts systems. The family is often shortlisted where reasoning and coding matter.
    Listed by Oumi

    Profile: DeepSeek

  • Llama

    Meta · United States
    Llama is Meta’s open-weight model family. Its wide ecosystem makes it a familiar baseline for teams evaluating or fine-tuning their first custom model.
    Listed by Oumi

    Profile: Llama

  • Mistral

    Mistral AI · France
    Mistral is a European model family spanning open-weight and commercial releases. The right starting point depends on the exact release and deployment constraints.
    Listed by Oumi

    Profile: Mistral

  • Gemma

    Google · United States
    Gemma is Google’s open-weight model family. It includes compact checkpoints that can be useful when hardware limits and deployment footprint drive the decision.
    Listed by Oumi

    Profile: Gemma

Oumi benchmark data is coming. We’ll add reproducible task benchmarks once the evaluation recipe, model version, dataset, hardware, and scoring criteria are published.

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Questions about the Atlas

  • What is the Atlas of AI?

    The Atlas of AI is a directory of specialist-model opportunities organized around business decisions and tasks. It helps you explore where a focused model may create value, then move toward evaluation and ownership.

  • How do I find a Specialist Model for my business task?

    Start with the business decision or repeated workflow you want to improve, then use Atlas filters and rankings to narrow the relevant category. Treat the result as a discovery hypothesis and validate it against your data, evaluation criteria, and deployment needs.

  • Which open-weight model should I start from?

    Start with the open-weight model that fits your task, quality target, context needs, license, hardware, and deployment constraints. There's no single best model for every workflow, so use Atlas evidence and your own evaluation set.

  • What evidence supports each Specialist Model listing?

    A listing is a structured starting point grounded in the task, model, benchmark, or other evidence shown with it. Review the evidence and run your own evaluation before treating a listing as a production recommendation.

  • Can I build a Specialist Model directly from the Atlas?

    The Atlas helps identify a promising task and starting model. From there, use Oumi's build and evaluation workflow to define behavior, assemble data, test the model, and decide whether to train and deploy it.

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