See the full customer picture, decide what matters next, and update the account in one place.
The first automated revenue engine
psi* is a quantitative machine that learns how to sell and operate your company. Its objective function is increasing your revenue.
Give psi* your operating data. It builds a living model of your company, runs the work across your GTM stack, and learns which actions create revenue—then does more of what works.
Agents and your team operate on the same runtime, sharing apps and flows.
Human and agent work stays inside one operating system instead of fragmenting across side tools, brittle handoffs, and disconnected automations.
Platform
From Your Data Get:
- Customer account recognition, identity resolution & deep enrichment
- Sales and marketing attribution
- Revenue recognition and vendor contract management for all products & services
- Revenue claims, P&L, AR, and smallest level of detail financials for every customer
- Sales Compensation credits, earnings, and payout ledger rows
How it works:
- Built as a data ingestion pipeline that feeds live data into your org's Digital Twin
- Ontology is built on top of a tenant-isolated Postgres with RBAC views over your data
- Immutable history record -- corrections are new claims, not edits
- Every module joins through the same Canonical Customer anchor so you have a source of truth
Org Intelligence overview
Company, people, and competitive landscape
Research your market, enrich accounts, map relationships, and visualize your competitive landscape — all maintained as a living model inside psi*.
Researches and models how your company exists in the world
- Your Company's Positioning: products, services, and capabilities alongside your people and relationships
- Your Potential Customers: problems your company solves mapped to ICPs, segments, and fit
- Your Competitors' Positioning: how differentiated they are and where they exist in the market
- Your Landcapse: A Graph of the above and their relationships, key personnel, and investor networks
And how it needs to act
- Gives your company a competitive positioning in the market
- Finds Potential Customers
- Updates with every customer interaction and how the market is changing
- Ingests data from your Ontology and optimizes your acquisition strategy
- Living model — not a static snapshot, continuously enriched
- psi* use classic machine learning techniques to optimize your acquisition strategy
Coworkers can do anything you can do in a psi* app
- The apps and flows you build become the harness your AI agents operate within
- Coworkers use apps through the psi* agent runtime, this takes any app you build and turns it into an environment for your agent
- Research accounts and run browser sessions
- Execute flows and delegate scoped build work
- Execute customer service requests that are scoped to your specific Customers
How they work
- Coworkers are called through Slack and operate your apps asynchronously.
- Coworkers maintain context across many channel sessions and have parameters for each app they use
- Apps bring in data sources and use strucutred queries to stay bounded, your agent cannot go ourtise these boundries
- Approvals stay attached to high-risk actions for your team to review
- Tools and writes stay scoped by your organization and app permissions for each coworker
- Everything runs inside one psi* cluster that is isolated to your organization
Context+Restrictions for Agents
- Every app defines the boundary of what an agent can see and do
- Structured queries and data sources keep agents scoped to your business logic
- The compiler emits an operability manifest the runtime enforces on every agent action
True collaboration
- Humans and agents work the same screens, forms, and approval lanes
- One published surface — no separate agent-only version to maintain
- Agents fill in the gaps: intake, routing, review, and follow-up while your team focuses on judgment calls
How apps ship
- Alls apps are git enabled and this allows you to A/B test agents and workflows easily
- Compile apps to ensure that they work and then publish them to create a runtime for people and agents to use
- Apps and flows are builts together and use queries against your data and JavaScript/Python to execute complex actions
- Published apps can be scoped to a public url so people and agents can use them
How flows and data work
- Apps, flows, and agents can share one managed workspace database or use your production data sources
- Flows trigger on schedule, webhook, app events, or manual start (so agents can trigger them)
- Flow function blocks run through the same Runtime Code Execution path
- Pause, retry, and approvals are first-class — no external orchestration needed

How sources connect
- Shim transforms normalize raw data into published outputs; FDW contracts certify them
- Ontology modules ingest through upsertable views to create accepted facts
How queries stay safe
- Query Studio: scratch, test, and promote queries into canonical app working state
- Provider Execution dispatches through a dedicated provider_worker, not the web process
- Credential Lease resolution is worker-local — plaintext never reaches API, browser, or logs
- Provider Catalog families: workspace-db, postgresql, http, oauth-saas, and exa
Apps people and agents share
People and agents use the same apps.
Choose an app to see how people do the work, how agents help, and how everyone stays on the same page.
Shared app
CRM
Accounts, contacts, deals, and activity history in one shared workspace.
Brings together the missing context and suggests useful next steps for the person working the account.
- 01 account signal
- 02 deal review
- 03 next action
Changes, ownership updates, and messages stay visible for people to review.
Shared app
Outbound Seller Workspace
Prospecting lists, sequences, call notes, and next steps for each rep.
Choose priority accounts, review the context, and decide which prospects should move forward.
Finds useful company details, drafts a starting point, and keeps the next step ready for review.
- 01 research accounts
- 02 prepare outreach
- 03 review before send
People can review every message and list change before it goes live.
Shared app
Live Selling Companion
Real-time account context, talk tracks, and objection handling during calls.
Keep the customer history, live notes, and next step in view while you are on the call.
Pulls up relevant details, records decisions, and turns follow-up promises into clear tasks.
- 01 open account context
- 02 guide the call
- 03 attach follow-up
The agent helps during the call but never sends or changes anything by itself.
Shared app
Customer Support Inbox
Triage, assign, and resolve tickets with full customer context attached.
See the customer history beside each request and focus the team on the most important work first.
Sorts new requests, gathers the useful details, and drafts a reply for someone to check.
- 01 triage request
- 02 assemble context
- 03 resolve with review
Sensitive changes and customer replies stay with the support team for approval.
Shared app
Returns & Refunds Portal
Submit, review, and approve return requests with automated status updates.
Check the request and customer details, then approve it or send an exception to the right person.
Checks the order details, gathers the facts, and keeps each update with the request.
- 01 verify eligibility
- 02 review exception
- 03 publish status
Refund decisions are clear, reviewable, and saved with the case.
Shared app
Inbound Lead Form
Capture, score, and route inbound submissions to the right rep instantly.
Review good-fit leads, confirm who should own them, and keep the handoff clear from the first form to the first conversation.
Looks up the company, checks whether it is a good fit, and prepares the lead for the right seller.
- 01 capture signal
- 02 score + enrich
- 03 route to owner
People can see and adjust the scoring and routing rules at any time.
Enterprise ready
Data store
Tenant-isolated Postgres
Each customer runs on an account-locked Postgres data plane for replicated operational data.
Access control
Restricted access rules
Users, groups, app access, and write paths stay governed from one system.
Replication
Anonymization at ingest
Sensitive data can be anonymized before replicated records become business-facing surfaces.
Approvals
Writes stay reviewable
Higher-risk actions can pause for approval instead of bypassing governance in side tools.
Enterprise data controls for startups.
Provision users, groups, approvals, and app access from one system instead of layering policy across disconnected vendors.
Each customer gets an account-locked ontology data plane for replicated operational data, with isolated boundaries and reviewable write paths.
AI-First Go-to-Market Platform
managed revenue systemReplace point solutions with one managed revenue system.
psi* gives startups a superpower: by integrating the entire GTM and RevOps stack into one platform you create a feedback loop that turns effort into revenue faster and faster.
Point solutions vs psi*
Comparable GTM scope for a sub-50-person team.
GTM-first AI enabled apps
- Published apps, forms, inboxes, and operator views
- One runtime for teams and agents using the same surfaces
Flows
- Cron jobs, recurring work, and routed automations
- Query, transform, and write in one platform
Data and approvals
- Approval-gated actions and reviewable writes
- Provision users and groups per app and workflow
Log in to psi*
Access your workspace to build, operate, and govern your company’s GTM system.