for software and AI-service teams running 3+ agents

Every agent starts
with the right context.

ValorBrain keeps decisions, facts and documents for every project and client in shared memory. Each agent gets what it needs, with the right source and permissions.

  • Claude Code
  • Codex
  • OpenClaw
  • Hermes
  • and other agents through MCP and API
See how it works in 40sTry it with one project
  • Sourced answers
  • Per-person permissions
  • Data in Brazil · LGPD
workspace · dashboardproduct UI
ValorBrain dashboard: Ask memory, workspace stats, and MCP connection
Real product UI. Shared memory gives connected agents the same sources, citations and current context.

See a sourced answer in 40 seconds.

One question, the retrieved context and the document behind the answer. No narration.

Many agents. One shared context.

With three or more agents, context becomes infrastructure. Decisions, client scope and permissions must stay consistent when the tool changes.

  • Each agent gets a different briefing
    Every agent starts from the same current decisions
  • Client context stays trapped in chats and people
    Each project and client keeps its own shared context
  • An old document quietly becomes the answer
    Sources stay visible and conflicting versions are flagged
  • Access rules have to be rebuilt in every tool
    The agent inherits the permissions of the person using it

Connect. Scope. Deliver.

Memory follows the work across projects, clients and agents without erasing access boundaries.

Connect

Start with the material you already have.

  • Google Drive, Notion, GitHub, Linear and Slack
  • Documents, transcripts and REST API
  • No data-modelling project before the first answer

Scope

Keep each project and client in the right boundary.

  • Shared or private sources
  • Roles and permissions inherited by the agent
  • Conflicting versions flagged before they become context

Deliver

Give the same current memory to every connected agent.

  • Context through MCP and API
  • Source attached so the answer can be checked
  • Decisions written back for the next agent

broad compatibility

The context stays when the agent changes.

Claude Code, Codex, OpenClaw and Hermes are familiar examples. The same memory is also available to other agents through MCP and API.

Claude CodeCodexOpenClawHermes+ other agents
  • Same context

    Agents retrieve the same current decisions for the project or client.

  • Right scope

    Each agent receives only the material allowed for that person and source.

  • Visible source

    The source travels with the answer, and conflicting versions do not pass silently.

published evidence

What the benchmarks actually measure.

LoCoMo measures whether the right evidence reaches the top 10. BEAM-100K measures the end-to-end answer across sessions. Isolation, permissions, and handoffs are outside these scores.

  • 96.58% evidence recall@10 on LoCoMo. +2.1 pp vs published open-source leader (94.5%)
  • 80.8% end-to-end binary accuracy on BEAM-100K (323/400 correct across 20 conversations; reader GLM-5.3 Flash (Ox Alpha); judge GLM-5.2; effort=max; run 2026-08-23; ~44% slower than default effort; this benchmark setup is not the chat default)
See method and results →See security and permissions →

Start with one project. Expand later.

Documents, memory and search are unlimited on paid plans. You pay for people and AI answers. Business free for 14 days, no card.

  • Free
    $0

    100 answers/mo

    1
    Try
  • Solo
    $20

    500 answers/mo

    1
    Try
  • Team
    $59

    2,000 answers/mo

    10
    Try
  • BusinessPopular
    $249

    10,000 answers/mo

    50
    Try
  • Enterprise
    Custom

    unlimited answers

    unlimited
    Try

Need more people, on-premise or a 99.9% SLA? Enterprise is negotiated. See full pricing →

Questions

What a team with several agents needs to know before trying it.

What problem does ValorBrain solve?
When a team runs several AI agents, project and client context gets split across prompts, chats, documents and people. ValorBrain keeps current decisions, facts and documents in shared memory, then gives each agent the right context with its source and permissions.
Which agents can use it?
Claude Code, Codex, OpenClaw and Hermes are familiar examples. Other compatible agents can use the same memory through MCP or the API, so the team is not limited to one vendor or one interface.
Who gets the most value from it?
Software teams and AI-service companies running three or more agents across projects or clients feel the problem first. You can start with one project and expand the same memory as more people and agents join.
How much does it cost?
On paid plans, documents, memory and search are unlimited. You pay for people and AI answers. The free plan covers 1 person, 1,000 documents, unlimited search and 100 sourced answers a month, with no credit card. Paid plans start at $20/month for 1 person, with unlimited documents and search. You can also run a 14-day Business trial with everything unlocked, no card.
Where is our data stored, and who can see it?
Documents and vectors are stored in Brazil under LGPD. Each person only sees what their role allows, and an agent asking on their behalf inherits the same boundary. Writing the answer uses a cloud language model with a publicly listed subprocessor; on-premise processing is available for customers who need it.
How long until we can test the first answer?
Connecting a source and asking the first question happen in the same setup flow. There is no data-modelling project or consulting engagement required before the team can test its own material.
Can we cancel whenever we want?
Yes, from your own settings, with no call and no notice period. Your data is permanently deleted within 30 days.

Stop re-explaining the work
to every agent.

Connect one project and bring the same context to the agents your team already uses. Business free for 14 days, no card.

Try it with one projectTalk about my workflow