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The Organizational Intelligence Platform

Praxa gives people and teams an AI agent that remembers how work gets done, runs real missions in the background, and asks before anything consequential.

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Features

Background missions

Delegate work that outlives the chat. Praxa keeps the context, runs the mission, and returns with a reviewable result.

Shared team context

Coordinate around one source of truth. Keep people, agents, decisions, and approvals attached to the work.

One working context across your personal agent, organizational memory, background missions, and connected control.

Most AI stops when the conversation stops. Praxa is built for the work that comes after: research that takes time, coordination that crosses tools, and decisions that need context before anyone acts.

Your agent carries continuity across chat, voice, mobile, and the web. It remembers useful working context, keeps sources attached to its conclusions, and turns a request into a mission with a visible state.

For teams, that continuity becomes organizational intelligence: shared knowledge that stays connected to the people, files, approvals, and outcomes that made it trustworthy.

Autonomy does not mean surrendering control. Praxa separates planning from committing, shows what an action will do, and pauses for human approval before consequential work moves forward.

The goal is simple: remove the coordination tax around meaningful work while keeping judgment, accountability, and the final decision with the person.

Missions that keep running

Move beyond one-shot answers with background work that keeps its context until the result is ready to review.

  • Persistent mission state
  • Source-backed research
  • Results delivered when complete
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Memory you can inspect

Praxa turns useful working context into memory that people can read, correct, and control.

  • Personal and team boundaries
  • Editable remembered context
  • Continuity across supported runtimes
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Approval before consequence

Praxa can prepare the work autonomously while keeping the final commitment with a person.

  • Preview the exact action
  • Confirm consequential steps
  • Keep an auditable record
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Praxa product principle

The agent can do the preparation, coordination, and follow-through. The person keeps the judgment, the approval, and the final word.

Know what your agent knows—and what it is doing

Praxa keeps sources, working context, mission state, and approvals visible so useful autonomy does not become a black box.

Connected work map

See how work connects. Keep missions, tools, people, and outputs attached to the context that produced them.

Inspectable memory

Understand the remembered context. Review, correct, or remove what Praxa uses to help next time.

Mission status

See what is queued, running, blocked, or ready for review.

Fast handoffs

Move from a conversation into a persistent mission without restating context.

Agenda context

Connect time, meetings, and priorities to the work the agent is doing.

Scheduled work

Run recurring or time-bound work with a visible owner and outcome.

One agent across your models, data, and tools

Praxa coordinates supported providers and connectors behind one working context while preserving the boundaries of each runtime.

See connectors
Infrastructure
Model providers
Cloudflare
Supabase
Google models
Anthropic

Useful autonomy with explicit boundaries

Praxa separates preparation from commitment, scopes tools by runtime, and keeps high-impact actions behind human approval.

Control that survives scale

Give more work to agents without making approval rules, access boundaries, or responsibility disappear.

  • Human approval for consequential actions
  • Inspectable memory and mission state
  • Deliberate per-runtime tool access
Read the security model

Scoped access

Keep personal, team, and organization contexts deliberately separated.

Fail-closed actions

Consequential operations refuse to proceed without the required approval.

Visible records

Keep the rendered approval, recorded payload, and action gate aligned.

Runtime boundaries

Cloud, voice, and on-device tools differ intentionally by capability.

Built around responsibility, not a demo reel

Praxa is designed to make agentic work more useful without hiding how it reached a result or who approved an action.

Autonomy is useful when the system can show its work, respect the boundary, and stop when approval is required.

How Praxa handles approval

Fail closed

No required approval, no committed action.

Sources, mission state, memory, and approval details stay visible so a result can be checked instead of merely trusted.

Inspectable by default

Praxa can prepare and coordinate the work while consequential commitments remain explicitly human-approved.

The person keeps the decision

Give the work somewhere to go

Start with one request. Praxa keeps the context, coordinates the mission, and returns when there is something worth reviewing.

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