Cognee vs h2oGPTe (2026)

Cognee

by Topoteretes

h2oGPTe

by H2O.ai

Pros

• ✓Knowledge graph memory is available on every tier including the free plan and the free self-hosted build, rather than being reserved for a paid upgrade. Agentic integrations covering Claude Code, Codex and MCP are also on the free tier.
• ✓ECL pipeline builds self-improving memory that gets sharper with use. Rated responses feed back into graph edge weights, so accuracy improves over time rather than staying static like vector-only systems.
• ✓Three official SDKs cover Python, TypeScript via @cognee/cognee-ts for Node.js, and Rust via cognee-rs, alongside a documented MCP server for Claude, Cursor, Cline, Continue and Roo Code. Self-hosting the open-source engine is free with no time limit, and the vendor documents running it on local models.

Limitations

• –Documentation depth is uneven across the three SDKs. The Python surface carries substantially more documented pages than the TypeScript and Rust surfaces, so teams outside Python should expect to read source and fill gaps.
• –Benchmark results are vendor-run. Cognee publishes its own BEAM scores and chain-of-thought gains on its evaluation page, but there is no third-party evaluation and no published LongMemEval result, so procurement teams comparing memory layers are working from the vendor's own harness.
• –Compliance coverage is thin for regulated buyers. Cognee states GDPR compliance and carries a CCPA section in its privacy policy, but publishes no SOC 2 Type II, no ISO 27001 and no certification set on its trust page, and its terms state no position on whether customer data is used for model training.

Pros

• ✓In a June 2025 press release, H2O.ai reported 79.7% accuracy for its h2oGPTe Agent on the GAIA benchmark of real-world assistant tasks, a published task-completion figure that procurement teams can check.
• ✓Air-gapped and on-premise deployment, SOC 2 Type 2 and ISO/IEC 27001:2022, plus a FedRAMP High certified government edition, suit regulated buyers in banking, government and healthcare.
• ✓Generative and predictive AI sit in one platform, with document AI, audio and vision models, guardrails, PII controls and routing across LLMs built in.

Limitations

• –There is no self-serve pricing. h2oGPTe is sold through sales on custom terms, and H2O.ai publishes no pricing page.
• –Most independent review evidence covers H2O.ai's wider platform rather than h2oGPTe itself, and the h2oGPTe iPhone app carries only a handful of App Store ratings.
• –The FedRAMP High certification belongs to H2O.AI for Government, a separate GovCloud edition, so commercial deployments should not assume it applies to them.