Dotwork vs Holistic AI
An AI governance platform for inventorying AI systems, scoring their risk and running assessment programs.
Holistic AI gives risk and responsible-AI teams a scored inventory of AI systems, with assessments, bias testing and compliance evidence. Dotwork places AI governance next to AI cost, value, ownership and the rest of the operating model, so the same AI asset can be followed from finding to owner to spend to the strategy it serves.
At a glance
AI governance
Holistic AI
Operating model
Dotwork
Overlaps with
Dotwork runs these and 15 more on one model.
Usually runs alongside Dotwork
Dotwork connects to it and puts its data in the context of the whole enterprise.
The short version
What each is built for.
Holistic AI
Holistic AI is an AI governance company with offices in London and San Francisco, founded in 2020. Its platform keeps an inventory of AI systems, scores their risk, runs assessments including bias and fairness testing, and tracks policies, controls and evidence for regulations such as the EU AI Act. This comparison refers to that company, not to other firms with similar names.
- Building a scored inventory of AI systems for the risk office
- Running risk assessments, including bias and fairness testing
- Tracking policy and control coverage and assurance evidence
- Preparing for AI regulations in Europe and the United States
Dotwork
Dotwork is an AI-native enterprise operating platform built on the Enterprise Operating Model: one live, graph-based model that connects strategy, capital, work, technology and AI across the enterprise. For AI governance, it places AI assets, findings and controls on the same records as AI spend, ownership and the initiatives that funded them.
- Inventorying AI assets alongside their owners, findings and controls
- Setting AI spend beside the value recorded for each initiative
- Tying security findings to owning teams and AI assets
- Placing AI governance in the same model as cost, architecture and strategy
The core difference
How Dotwork and Holistic AI approach the problem.
Holistic AI approaches AI governance as risk management, built around an inventory, risk scores and assessments. Dotwork approaches it as part of the operating model, where each AI asset is also a cost, an owner and a funded commitment.
Context
Holistic AI's context is the AI system and its risk: how it scores, what assessments show and which controls apply. Dotwork's context is the AI estate as part of the enterprise: assets, owners, teams, spend, findings and the initiatives they support.
Decisions
Holistic AI supports risk decisions: where risk is highest, which systems need assessment and what evidence is needed. Dotwork supports accountability and value decisions: who owns an AI asset, what it costs and whether it is worth it.
Time
Holistic AI keeps risk scores and assessments current as AI systems and regulations change. Dotwork keeps AI assets, findings, incidents and approvals as records with history, next to spend by period.
Change
Holistic AI updates its assessments and regulatory content as rules evolve. Dotwork extends its reference operating model, so new AI assets and controls connect to the cost and strategy records already in place.
Architecture and data model
Side by side.
Holistic AI is built to show a risk office where AI risk sits and how it is being managed. Dotwork is built to show leaders what their AI estate costs, who owns it and what it returns, with governance records on the same model. Risk-led organizations often run both.
| Dimension | Holistic AI | Dotwork |
|---|---|---|
| Core data model | An inventory of AI systems with risk scores, assessments and evidence | A graph of AI assets, owners, findings, controls, spend and initiatives |
| Risk assessment | Risk scoring and assessment workflows as the daily practice | Model risk assessment at a foundational level |
| Bias and fairness | Bias and fairness testing of AI systems | Not offered |
| Evidence and compliance | Policy and control coverage with assurance evidence | Records incidents and approvals for agent actions; does not run audits |
| Cost and value | Focused on risk and compliance rather than AI cost | AI spend in the cost model, set beside the value recorded for each initiative |
| Ownership | Named owners and findings on each AI system in the inventory | Findings tied to owning teams, AI assets and their spend |
The role of AI
Where the AI gets its context.
Holistic AI's approach serves the risk office. Dotwork's AI works across the operating model, so a governance question can continue into cost, ownership and strategy.
Holistic AI
Holistic AI governs AI systems by inventorying them, scoring their risk and testing them for issues such as bias, with workflows that help risk teams run their assessment program.
Dotwork
Dotwork's assistant answers questions across the whole operating model, and its agents can create and update Dotwork records, pausing a change for human approval when review is required. An MCP server, enabled per site, gives outside AI tools access to the same graph.
A fair comparison
Where Holistic AI is strong — and where Dotwork is different.
Where Holistic AI is strong
- Its risk dashboard on top of an AI inventory gives a risk office a clear first view of the AI estate.
- It is strong on AI inventory, named owners, model risk assessment, and policy and control coverage.
- It tests AI systems for bias and fairness, a capability Dotwork does not offer.
- Assurance evidence and security findings are well supported, and controls that are not yet met stay visible.
- Its presence in London and San Francisco suits organizations preparing for both EU and US AI regulation.
Where Dotwork is different
- Sets AI spend beside the value recorded for each initiative, so AI investments can be reviewed against what they cost.
- Places AI spend in the enterprise cost model, connected to the AI assets that consume it.
- Ties security findings to the owning teams, AI assets and spend involved.
- Records incidents and approvals for agent actions next to the assets they affect.
- Connects AI assets to applications, capabilities and the strategy that funded them.
Choosing
Which fits your situation.
Choose Holistic AI when
- Your risk office needs a scored inventory of AI systems
- You need bias and fairness testing as part of assessment
- You are building an AI risk assessment program for EU and US regulation
Holistic AI fits AI risk and responsible-AI leads who want a scored AI inventory, an assessment program and bias testing they can run day to day.
Choose Dotwork when
- Leaders ask what each AI asset costs, who owns it and whether it is worth it
- Findings and controls need to connect to owning teams and spend
- AI governance should sit on the same model as cost, architecture and strategy
Dotwork fits organizations where AI governance has to sit next to AI cost, value, ownership and the rest of the operating model.
The bottom line
Choose Dotwork when you want to connect the enterprise across systems and silos — with a lower total cost of ownership.
One operating model across strategy, capital, work, technology and AI, instead of another tool to integrate, reconcile and maintain alongside Holistic AI.
FAQ
Questions buyers ask.
Can Dotwork and Holistic AI be used together?+
Yes. Holistic AI remains the risk and assessment layer, and Dotwork connects AI assets to their owners, findings, spend and the initiatives they support.
Does Dotwork test models for bias?+
No. Bias and fairness testing is not part of Dotwork. Holistic AI and other specialist AI governance tools cover that work.
Does Dotwork score AI risk?+
Dotwork includes model risk assessment and a framework crosswalk at a foundational level. Holistic AI's risk scoring and assessment workflows are deeper, and risk offices that run a full assessment program typically rely on a specialist tool.
Keep comparing
Buyers also compare Dotwork with
Be Decisive.Build Fast.Connect Everything.
Start ConnectingSolutions
Platform
Resources
© 2025-2026 Dotwork, Inc. All rights reserved.