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A local control plane for AI agents.

Valdr is a desktop app that plans work, runs agents, builds source-aware Workspace Knowledge across your projects, preserves context in Agent Memory Notebooks, scores every session across seven dimensions, and requires human approval before anything ships. It runs on your machine — your data stays with you.

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Outcomes

What changes when agent work is structured, scored, and reviewed.

Tasks are review-ready before agents run

Every task has an owner, acceptance criteria, and an approval policy before execution starts.

Agents stay inside their boundaries

Agents are scoped to approved projects and tools. Risky steps pause for human review before code reaches a release branch.

Full audit trail for every decision

Prompts, tool actions, and seven-dimension scorecards are captured in one timeline reviewers can check quickly.

Reviewers get evidence with the work

The scorecard and session transcript ship with the output, so reviewers don't have to reconstruct context.

Scoring catches problems before you ship

Run a seven-dimension score on any session before approving it. Low scores surface issues so reviewers know where to focus.

Context survives across projects

Workspace Knowledge, capabilities, and Agent Memory Notebooks keep standards, dependencies, decisions, and lessons available without re-explaining them every session.

Platform features

What this looks like in practice

A task goes from idea to shipped code with full traceability at every step.

The shift

From ad-hoc prompting to structured delivery

Most agent workflows are a loop: prompt, hope, manually verify. Valdr replaces that with a defined path — plan the work, run agents within boundaries, score the output, and require human approval before anything ships.

Before

  • You re-explain project conventions every time you start a new agent session.
  • Agent output lands with no record of what it was told to do or why it made certain choices.
  • Cross-project dependencies require manual spelunking before an agent can make a useful change.
  • Important lessons sit in chat history instead of becoming reusable project memory.

After

  • Agents inherit task context, acceptance criteria, coding standards, and cross-project Workspace Knowledge — no re-explaining.
  • Every session records the full execution trail: prompts, tool calls, changes, and scores.
  • Code map queries let agents trace definitions, callers, references, docs, and related code across attached projects.
  • Agent Memory Notebooks turn hard-won context into scoped memory the next session can retrieve.

How it works

  1. 1

    Define the work

    Set goals, acceptance criteria, and owners before agents start.

  2. 2

    Run with context

    Agents execute within approved scopes, use Workspace Knowledge for cross-project deep dives, and pause when they need human input.

  3. 3

    Review and ship

    Check the scorecards and evidence, then approve or block.

How Valdr stays honest

No cloud dependency, no silent data collection, no shipping without review.

Local-first by default

Keep execution and audit records inside your environment unless you explicitly connect external services.

  • No vendor data retention by default
  • Offline-ready runtime

Review before publish

Workflows include explicit approval checkpoints so teams can enforce quality before release.

  • Human checkpoints in every run
  • Clear ownership and handoff

Evidence-backed governance

Sessions are scored with inspectable context so teams can trace why outcomes passed or failed.

  • Seven-dimension scorecards
  • Actionable audit trail for remediation

Pricing

Snapshot of the three tiers with a clear path to the full comparison.

Raider

Free forever. Full UI, local runtime, manual workflows.

Who this is for: Individual builders evaluating Valdr or running manual agent workflows.

$0 / month

  • Full Valdr UI — dashboard, tasks, sprints, reviews
  • Prompt and capability library
  • Local-only runtime, offline-friendly setup
  • No MCP tool access — UI driven only
  • +1 more in full comparison
Use Raider (Free)

Vanguard

MCP access to PM tools. Automate tasks, sprints, and reviews.

Who this is for: Builders who want agents to read and write project data through MCP tools.

Most popular

$25 / month

  • Everything in Raider
  • Seven-dimension session scoring
  • MCP access to Tasks, Sprints, Reviews, and Projects
  • MCP access to Agents, Capabilities, and Prompts
  • +2 more in full comparison
Subscribe to Vanguard

Sovereign

Workspace Knowledge, Agent Memory Notebooks, and session orchestration.

Who this is for: Power users building agents that deep-dive across projects, retain memory, chain reviews, and orchestrate delivery.

$50 / month

  • Everything in Vanguard
  • Workspace Knowledge MCP — source-aware context across projects
  • Agent Memory Notebooks scoped by project or workspace
  • MCP access to Sessions — spawn and manage agents
  • +4 more in full comparison
Subscribe to Sovereign

Raider requires no credit card. Paid tiers are monthly subscriptions with cancel-anytime billing.

View full pricing details

Need every capability side-by-side? Open the full `/pricing/` breakdown.

FAQ

What is Valdr?
A desktop app that plans, runs, and scores AI agent work locally on your machine. It adds structure — tasks, owners, acceptance criteria, scoring, and human review gates — so agent output is traceable and reviewable before it ships.
Where is my data stored?
On your machine or private network. We don’t copy it to our servers.
Can agents remember project context?
On Sovereign, agents can use Workspace Knowledge to search across projects, then preserve reusable findings in Agent Memory Notebooks. They can retrieve attached docs, runbooks, code context, references, and prior memory instead of starting from scratch every time.
Does Valdr send data to outside services?
Local‑only mode keeps core runtime data in your environment. If you connect a tool or model, you decide what leaves and when.
Can we run Valdr offline?
Valdr is offline‑friendly and well suited to private-network or high‑sensitivity environments.
Do you collect telemetry or analytics?
No background telemetry — diagnostics are opt‑in only.
How do approvals work?
Sensitive steps require a human review. Nothing ships without your sign‑off.
Will this slow us down?
Use review rules for sensitive work; let trusted steps run automatically.
Local‑only
No telemetry
Human review
Offline‑friendly

Security & Privacy

Control where your data lives—and who sees it.

  • Local‑only: Run Valdr on your machine or private network—no vendor cloud required.
  • No silent telemetry: We don’t phone home. You choose what’s shared, if anything.
  • Human‑in‑the‑loop: Sensitive steps pause for review. Nothing ships without approval.
  • Clear boundaries: You decide which projects, files, and agents have access.
  • Easy to verify: Local deployment with clear boundaries for high‑sensitivity work.

Get started with Valdr

Raider is free forever. Paid tiers unlock MCP access and advanced orchestration.

Start with Raider (Free)View full pricing