TinyHumans
Summary
Most AI assistants forget everything the moment you close the tab — context you spent weeks building resets to zero every session. TinyHumans Intelligence is built specifically around that failure, pairing a local-first desktop agent (OpenHuman) with persistent memory infrastructure (NeoCortex) so context survives across sessions, tools, and weeks.
OpenHuman runs as a desktop app, keeping memory and agent execution on your machine rather than a vendor's cloud — which means your work context, preferences, and knowledge base don't get packaged and sent upstream. NeoCortex handles the memory layer as an API, targeting teams who want deterministic recall baked into production applications. The agent layer is genuinely agentic: the vendor page describes joining meetings, executing code, controlling browsers, and running scheduled tasks autonomously. Where this architecture shows its limits is the managed backend services — even OpenHuman requires account sign-in and model routing that connect to TinyHumans-operated infrastructure, so 'local-first' is partial, not absolute. Teams needing fully air-gapped deployments will hit that wall.
Bottom line: Pick this if you're building a context-aware personal agent or need a memory API that survives across long-running workflows — but plan a different architecture if your compliance requirements demand fully air-gapped, zero-external-call infrastructure.
Pricing Plans
Usage-Based- Free Tier
- NeoCortex: 500k Intelligence tokens/month, 100MB raw data, limited documents and memories. OpenHuman itself is open-source but may require subscription for cloud services like model routing.
NeoCortex Free
Get started with no credit card required
- Generous free limits for development and testing
- 500k Intelligence tokens per month
- 100 MB raw data processed per month
- Limited document and memory quota
NeoCortex Usage-Based
Scale with usage, top up anytime
- $1 per GB of raw data processed
- $1 per 1 million Intelligence tokens consumed
- No monthly caps or limits
- Pay only for what you use
View full pricing on tinyhumans.ai →
Pricing may have changed since last verified. Check the official site for current plans.
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Pros
Sign in to edit- Persistent memory across sessions, so agents accumulate work context over weeks instead of resetting to zero on every launch — which eliminates the re-briefing overhead that makes most AI assistants impractical for ongoing projects.
- Local-first storage via OpenHuman, so your knowledge base and preferences stay on-device rather than being indexed by a cloud vendor — which matters for users handling sensitive research or proprietary workflows.
- NeoCortex API exposes the memory layer to production applications, so teams can build context-aware agents without rolling their own vector store and retrieval logic from scratch.
- Autonomous agent execution — browser control, code execution, meeting participation, scheduled tasks — so multi-step workflows run without requiring manual handoffs at each step.
- Self-hosted option exists, so teams with infrastructure preferences are not locked into a single deployment model.
Cons
Sign in to edit- OpenHuman's 'local-first' claim is partial: account sign-in and model routing connect to TinyHumans-managed backend services, meaning data does leave the device at the infrastructure layer. Teams under formal compliance requirements — HIPAA, SOC 2, air-gap mandates — hit this wall immediately and will route to a fully self-hostable alternative like a locally-deployed open-source agent stack.
- The scraped page content provides minimal technical depth on rate limits, latency guarantees, or retrieval precision for NeoCortex — which means teams evaluating it for high-stakes production use have precious little to benchmark against before committing engineering time to integration.
- With no named alternatives in the market data and a thin public footprint (community links but sparse documentation signals), teams that need proven enterprise support SLAs or a large peer community for troubleshooting will find the risk profile harder to justify against established memory infrastructure providers.
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About
- Platforms
- macOS, Windows, Linux
- API Available
- Yes
- Self-Hosted
- Yes
- Last Updated
- 2026-06-01T09:29:02.195Z
Best For
Who it's for
- Developers and builders wanting local-first AI agent infrastructure
- Privacy-conscious users who want persistent memory without cloud vendor lock-in
- Teams integrating production AI with deterministic memory recall
- Power users needing context-aware assistants across multiple work tools
What it does well
- Building persistent personal AI agents that remember work context and preferences across weeks
- Automating multi-step tasks like email summarization, document organization, and calendar management
- Integrating AI memory into production applications via NeoCortex API
- Managing research and knowledge bases with local-first storage and retrieval
Integrations
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Frequently Asked Questions
- Is TinyHumans free?
- TinyHumans is a paid tool. No permanent free tier is offered.
- Is TinyHumans open source?
- No — TinyHumans is a closed-source tool. Source code is not publicly available.
- Does TinyHumans have an API?
- Yes. TinyHumans exposes a developer API. See the official documentation at https://tinyhumans.ai for details.
- Can I self-host TinyHumans?
- Yes. TinyHumans supports self-hosting on your own infrastructure.
- When was TinyHumans released?
- TinyHumans was first released in 2025.
- What platforms does TinyHumans support?
- TinyHumans is available on: macOS, Windows, Linux.
Hours Saved & ROI Stories Community
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TinyHumans Intelligence ships two products that work together: OpenHuman, a desktop application for personal AI agents that retains memory and preferences across sessions, and NeoCortex, a freemium API that provides the underlying memory infrastructure for production applications. The core workflow centers on persistence — agents remember what you worked on last Tuesday, adapt to your preferences over time, and execute multi-step tasks like email summarization, document organization, and calendar management without requiring the user to re-establish context each session. The agent layer supports autonomous execution: joining meetings, browser control, code execution, and scheduled tasks run without requiring you to manually trigger each step.
The differentiating feature is the memory architecture. Most agent frameworks treat memory as a session variable — it resets. NeoCortex treats memory as infrastructure: indexed, retrievable, and callable via API at $1/GB and $1/1M tokens on paid tiers, with a free tier for lower-volume use. For developers building production applications where context continuity matters — think support agents that remember a customer’s history, or research tools that accumulate a growing knowledge base — this is the layer that prevents context-from-scratch rebuilds on every call.
OpenHuman targets privacy-conscious users who are unwilling to route everything through a cloud AI vendor. The local-first framing is real: storage and retrieval run on-device. The caveat is that managed backend services — account authentication, model routing — still connect to TinyHumans-operated infrastructure. Teams with strict data residency or air-gap requirements need to audit exactly which calls leave the machine before committing. For users who are privacy-sensitive but not compliance-constrained, this is a meaningful step up from fully cloud-dependent alternatives. For teams under formal compliance regimes, the ‘local-first’ label requires scrutiny.