LatticeFlow AI vs Saidot
Side-by-side comparison of framework coverage, pricing, capabilities, and target customers. Last verified recently.
https://aicompliancevendors.com/compare/latticeflow-ai-vs-saidotLatticeFlow AI
A single platform to discover, evaluate and govern risk to secure your AI future.
LatticeFlow AI is a Swiss deep-tech company headquartered in Zurich, spun out of ETH Zurich in 2020, that provides a platform for AI security and governance centered on deep technical evaluations. The company co-created COMPL-AI, the first open-source evaluation framework mapping EU AI Act requirements to concrete technical controls for generative AI, in partnership with ETH Zurich and INSAIT. This positions LatticeFlow AI as a primary reference for EU AI Act compliance-centered AI assessments. The platform covers agentic AI risk assessment, foundation model risk screening, automated AI security red-teaming, and continuous AI governance operations. It is listed in the 2025 Gartner Market Guide for AI Governance Platforms and the 2025 Gartner Market Guide for AI TRiSM. Customers include global wealth management institutions, Axpo (energy), defense organizations, and Swiss Federal Railways.
Saidot
EU-native SaaS platform for AI governance — easy to start, efficient to maintain.
Saidot offers a SaaS platform for AI governance that connects AI system inventories with knowledge graphs of risks, models, and controls to automate risk identification, mitigation suggestions, and compliance workflows. Targeted at enterprises and governments, particularly in Europe, it supports safe AI deployment through features like automatic control inheritance, step-by-step EU AI Act templates, evidence reuse across systems, and integration with existing GRC tools. Its knowledge graph enables dynamic updates as AI components change, distinguishing it by reducing manual governance efforts and enabling scalable, adaptive compliance for both in-house and third-party AI. The platform serves public and private organizations, with case studies in financial services, human resources, and media.CB Insights profile Saidot product page Saidot homepage
What the data shows
We haven't published an editorial verdict on this pair yet. The comparison below is built from public vendor materials and our taxonomy — no editorialized ranking.
- Shared framework coverage: EU AI Act, ISO/IEC 42001, NIST AI RMF
- Shared capabilities: 9 of 10 listed.
Want our editorial take? Email the editors or read our methodology.
At a glance
| Attribute | LatticeFlow AI | Saidot |
|---|---|---|
| Founded | 2020 | 2018 |
| Headquarters | Zurich, Switzerland | Helsinki, Finland |
| Employees | 11-50 | 11-50 |
| Funding | Series A, $12M raised (October 2022), led by Atlantic Bridge and OpenOcean with participation from FPV Ventures. Prior seed of $2.8M (January 2021). | Seed, €1.75M ($1.84M), 2023, led by Crowberry Capital and Ventic; Business Finland |
| Pricing | No public pricing. Enterprise platform sold via direct sales. Contact sales for demo and pricing. | No public pricing listed; contact sales implied via demos and sign-ups. |
| Website | Visit site | Visit site |
Framework coverage
| Framework | LatticeFlow AI | Saidot |
|---|---|---|
| EU AI Act | Full | Full |
| ISO/IEC 42001 | Full | Partial |
| NIST AI RMF | Full | Partial |
Capabilities
| Capability | LatticeFlow AI | Saidot |
|---|---|---|
| AI Model Inventory | ✓ | ✓ |
| Audit Evidence Collection | ✓ | ✓ |
| Bias & Fairness Testing | ✓ | ✓ |
| Explainability | ✓ | ✓ |
| LLM Red Teaming | ✓ | ✓ |
| Model Monitoring | ✓ | ✓ |
| Policy Management | ✓ | ✓ |
| Regulatory Intelligence | ✓ | ✓ |
| Risk Assessment Workflow | ✓ | ✓ |
| Third-Party AI Vendor Risk | — | ✓ |
Industries served
LatticeFlow AI
- Financial Services
- Defense & National Security
- SaaS & Technology
Saidot
- Financial Services
- Government & Public Sector
- Employment & HR
- Insurance
Integrations
LatticeFlow AI
- OpenAI API
- GitHub
Saidot
- Azure ML
- OpenAI API
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Editorial independence: This comparison is free and was not paid for by either vendor. See our methodology.