Versuno AI
Open-source, local-first Postgres memory engine for AI agents with human conflict review.
Versuno is a solid pick for developers building MCP-compatible agents who need persistent memory without vendor lock-in. The memloom engine is genuinely open and free to self-host, with conflict review that saves you from silent data corruption. But if you're not comfortable with APIs and CLIs, this isn't for you—there's no gentle chat UI here.
Verified 2d ago · liveness 76/100 · cite: rightaichoice.com/tools/versuno-ai
- Developers building MCP-compatible AI agents
- Teams needing a shared context layer
- Organizations with technical teams
- Projects requiring agent-driven memory
- Users needing a simple chat UI or GUI
- Non-technical teams without API/CLI comfort
- Organizations needing on-premise deployment
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Skip Versuno if you need a simple chat-based memory solution with no API/CLI comfort, or if you require on-premise deployment—currently there's no support for it and no hosted cloud option beyond the coming-soon memloom cloud.
Exceeding the free tier's 2,000 public brain queries or 50 chat messages per month will require upgrading to Pro or buying credit packs, which start at $5 for 5,000 queries.
Versuno's pricing is usage-based and developer-friendly: Free tier for experimentation, Pro at $19/month for serious builders, and Team at $89/month for fast-moving teams. It's cheaper than OpenAI's Assistants API for many workloads, and the open-source memloom offers a self-hosted alternative. Compared to LangChain memory, Versuno's built-in conflict resolution and single-database approach may justify the cost for teams that value reliability.
In short
Versuno AI — Open-source, local-first Postgres memory engine for AI agents with human conflict review. Best for Developers building MCP-compatible AI agents, Teams needing a shared context layer, Organizations with technical teams. Free to start; paid plans from $5/mo.
What's new in Versuno AI
Checked 2 days agoAcross the latest 5 updates: 4 feature updates and 1 launch.
Introducing memloom: a local-first memory engine for AI agents
Versuno announces the launch of memloom, an open-source, local-first memory engine for AI agents, free to use.
Agents self-signup for Versuno
AI agents can now create Versuno accounts autonomously with working API keys, no human in the loop.
Public Brains: clean, up-to-date context for coding agents
Public Brains provide agents clean runtime context via API and MCP to combat hallucinations.
Versuno v0.6: RBAC & new onboarding
Versuno v0.6 adds role-based access control and a new onboarding flow.
Team Workspace is live
Team Workspace is now available in Versuno for collaborative context management.
What people actually say about Versuno AI — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
23 mentions across 1 source (YouTube) · researched Aug 17, 2026.
- +Open-source engine under Apache-2.0 — transparent and auditable.
- +Runs fully locally via PGLite for offline development and testing.
- +Unified relational, vector, keyword, and graph retrieval in one DB.
- +Conflict resolution with human-in-the-loop review prevents silent overwrites.
- +Public Brains deliver fresh context to coding agents, cutting hallucinations.
- −Zero community feedback or user reviews available anywhere.
- −No evidence of reliability or performance in real-world use.
- −Human-in-the-loop review may disrupt fast autonomous workflows.
- −Requires Postgres—a hurdle for teams not already using it.
- −Support quality unverified due to lack of reported feedback.
- • Credit packs that never expire could encourage overspending if not tracked.
- • Over-usage charges on API calls may accumulate quickly for production agents.
- • Postgres hosting and maintenance costs are separate and not included.
Viability Score
How well maintained and how widely used is Versuno AI? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- Open-source memory engine (memloom, Apache-2.0)
- Runs on Postgres, including local via PGLite
- Relational, vector, keyword, and graph retrieval in one DB
- Conflict resolution with human-in-the-loop review
- Every change can be reverted
- Public Brains for coding agents via API and MCP
- Private brains for team-specific context
- Agent self-signup with API key generation
- Agents decide what to remember (agent-driven memory)
- Structured context: decisions, skills, prompts, assets
- MCP (Model Context Protocol) support at v0
- Public API v0 for programmatic access
- CLI v0 for scripting and automation
- Role-based access control (RBAC) since v0.6
- Agent Skills: write once, reuse everywhere
About Versuno AI
Versuno is the company behind memloom, an open-source memory engine for AI agents that builds on Postgres and can run fully local via PGLite. The engine is Apache-2.0 and TypeScript-based, giving developers full code access so what runs on a laptop is byte-identical to production. At its core, memloom changes how agents handle conflicting memories: instead of silently overwriting, it surfaces contradictions to a human for review, and every change can be reverted. All retrieval modes—relational, vector, keyword, and graph—run inside a single Postgres database, eliminating the need to glue together multiple stores. For developers building coding agents, Versuno's Public Brains deliver clean, up-to-date context through API and MCP, cutting down hallucinations and session forgetfulness. Private brains keep team knowledge secure, and agents can self-signup, autonomously creating accounts and API keys. The platform offers a rich editor with reusable blocks, role-based access control (v0.6), and collaboration on prompts, decisions, skills, and assets—modeled after the Agent Skills feature for writing once and reusing everywhere. Programmatic access comes via a public API v0, CLI v0 (both live since April), and MCP v0. Pricing is usage-based with a free tier, Pro at $19/month, and Team at $89/month, plus never-expiring credit packs. Versuno is a practical alternative to closed memory solutions like OpenAI's Assistants or LangChain memory, especially for teams that value inspectability, local-first control, and the flexibility of an open-source engine.
Behind the Verdict
Versuno's memloom engine is a breath of fresh air in a market full of opaque memory solutions. The open-source, Apache-2.0 license means you can audit every line of code, and the local-first PGLite support ensures your data never leaves your machine if you don't want it to. The conflict resolution is the standout: instead of silently overwriting, memloom flags contradictions for human review, which is a huge trust win for agent-driven workflows. Strengths: The single Postgres database for all retrieval modes (relational, vector, keyword, graph) is elegant and simplifies your stack. The MCP v0 support means you can plug this into Claude, Cursor, or any MCP-compatible agent today. The Agent Skills feature lets you write once and reuse across your team, and the RBAC (v0.6) is solid for growing teams. The pricing is transparent, with a generous free tier and credit packs that never expire. Weaknesses: The tool is unapologetically developer-focused. There's no chat UI; you'll be interacting via API and CLI. The free tier's 2,000 queries and 50 chat messages per month are tight for anything but light experimentation. The Team tier pools 60,000 queries across 5 members, which can get exhausted fast if you have power users. The hosted memloom cloud is still 'coming soon,' so if you want a managed service, you're stuck with the Versuno platform for now. Where it fits: Solo developers and startups building coding agents that need reliable memory. Teams that want a shared context layer to avoid re-teaching agents. Organizations that value inspectability and local-first control. Where it doesn't: Non-technical teams or anyone expecting a polished GUI. Enterprises needing on-prem deployment (not mentioned). Teams that want a turnkey solution without touching code. Verdict: If you're a developer building MCP-compatible agents, Versuno is worth a serious look. It's cheaper and more open than OpenAI's Assistants, and the human-in-the-loop conflict review is a differentiator. Just be ready to get your hands dirty with APIs.
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Real-world workflow fit
Concrete scenarios for the personas Versuno AI actually fits — and what changes day-one when you adopt it.
You want to give your agent persistent memory of your project's conventions and past decisions without context loss.
Outcome: You set up memloom locally with PGLite, define a Public Brain with your framework docs, and your agent uses MCP to query it, reducing hallucinations and session forgetfulness.
You need a shared context layer so all agents and team members recall the same decisions and prompts.
Outcome: You create a Private Brain, add team members on the Team plan, and use Agent Skills to write once and reuse everywhere, ensuring consistent behavior across sessions.
You want to import assets from various AI chat apps and organize them for reuse across client projects.
Outcome: You use the Import with AI feature to automatically organize your prompts and decisions, and then share them as Public Brains for recurring client work.
Use Cases
- Equip your coding agent with up-to-date framework conventions from public brains to reduce hallucinations.
- Build a shared team brain that persists decisions, architecture notes, and prompts across sessions.
- Let your agent autonomously save and recall learnings from previous interactions.
- Centralize context from Notion, Slack, and files into one agent-accessible layer.
- Accelerate onboarding by giving new agents access to accumulated team knowledge.
Limitations
- Free tier limited to 2,000 public brain queries and 50 chat messages per month.
- Pro and Team tiers increase limits but still cap at 60,000 queries (Team). memloom is open-source and can run fully local, but hosted cloud is coming soon.
as of 2026-08-31
Verification history
We have re-verified Versuno AI 7 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 7 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Versuno AI tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Individual developers exploring memory solutions and building initial prototypes with light usage.
What this tier adds
Free entry point with 2,000 public brain queries, 50 chat messages/month, 10 private assets, and 10 projects.
Pro
$19/mo
Ideal for
Serious builders and solo developers who need higher usage limits and unlimited private assets/projects.
What this tier adds
Upgrades to 12,000 queries, 500 chat interactions/month, unlimited private assets and projects, plus priority support.
Team
$89/mo
Ideal for
Fast-moving teams of up to 5 members who need pooled usage and collaboration features.
What this tier adds
Adds 60,000 pooled queries, 2,500 pooled chat interactions, team prompt & asset library, role-based access, and priority support.
Starter Credit Pack
$5
Growth Credit Pack
$12
Developer Credit Pack
$25
Where the pricing makes sense
The company stage and team size where Versuno AI's pricing actually pencils out — and where peers do it cheaper.
Versuno's pricing is usage-based and developer-friendly: Free tier for experimentation, Pro at $19/month for serious builders, and Team at $89/month for fast-moving teams. It's cheaper than OpenAI's Assistants API for many workloads, and the open-source memloom offers a self-hosted alternative. Compared to LangChain memory, Versuno's built-in conflict resolution and single-database approach may justify the cost for teams that value reliability.
Setup time & first value
How long it actually takes to get something useful out of Versuno AI — broken out by persona, not the marketing-page minute.
For a solo developer, you can have memloom running locally with PGLite in under 30 minutes, following the docs. Connecting it to an MCP-compatible agent adds another 15 minutes. For a team, allow about an hour to set up the workspace, invite members, and define initial brains. Non-technical users may need more time due to the API/CLI focus.
Switching to or from Versuno AI
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From LangChain Memory: Export your conversation history and import it as assets via the API or CSV import feature.
- →From OpenAI Assistants: Move your thread data into Versuno's structured context (decisions, prompts) using the import tool.
- →From a custom Postgres setup: Point memloom to your existing database and start using its retrieval modes without re-architecting.
Integrations
Resources & Guides
Tutorials & Learning
Official links
Tools that pair well with Versuno AI
Common stack mates teams adopt alongside Versuno AI, with the specific reason each pairing earns its keep.
Featured Head-to-Head Comparisons
Versuno Ai vs Spider Cloud
Choose Versuno AI if your agents need persistent, structured memory and context to reduce hallucinations and avoid re-teaching. Choose Spider Cloud if your primary need is fast, reliable web data extraction for RAG pipelines. They solve different problems—Versuno retains internal knowledge, Spider Cloud fetches external data.
Versuno Ai vs Presto Voice
Versuno AI and Presto Voice serve completely different markets: one is a developer tool for AI agent memory, the other is a drive-thru voice AI for QSR chains. Choose Versuno if you're building AI agents that need shared, persistent context. Choose Presto if you operate a multi-location drive-thru chain and want upselling automation. There is no direct competition.
Versuno Ai vs Temporal Ai
Choose Versuno AI if your primary need is persistent, structured memory for AI agents to reduce hallucinations and retain context across sessions. Choose Temporal AI if you need reliable execution of complex, long-running workflows with automatic retries and crash recovery. They solve different problems: memory versus durability.
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