Platform / Prospect Intelligence

Know who to ask, before you ask them.

Researching a major donor or foundation by hand means a dozen browser tabs, a guess at how much to ask for, and no record of why you approached them that way. Prospect Intelligence runs a 51-agent research pipeline against one prospect at a time — discovery, deep background, relationship mapping, mission-fit and capacity scoring, and a cultivation strategy — and hands you a single evidence-backed dossier instead.

Build My Prospect MapSee how the pipeline works

Where this actually stands today

Prospect Intelligence is real, working code — not a mockup or a roadmap slide. It has its own database schema, a staff-facing dashboard inside the platform (research monitor, prospect list, agent activity, human review queue), and a working orchestrator that drives a research run through all nine agent families end to end.

What it isn’t yet: turned on for every organization. Access is gated behind a single organization-level rollout flag that defaults to off — if the flag service is unreachable or unset for your organization, the feature stays hidden rather than opening up by accident. The platform’s own rollout plan (a small named pilot group first, then a wider expansion, then general availability) hasn’t started yet. We’d rather tell you that plainly than show you a screenshot that implies your account can use this right now.

Ask about early access

Watch a research run move through the pipeline

Each step below mirrors a real stage in the orchestrator (src/lib/pil/research-orchestrator.ts).

ANIMATED SEQUENCE — ILLUSTRATES THE REAL FAMILY ORDER, NOT A SCREEN RECORDING
1. Supervisory — plan the research
A Chief Prospect Intelligence Orchestrator turns a goal (a name, or a natural-language request) into a structured research plan, allocates a token and dollar budget for the run, and a critic agent reviews the plan before any research starts.

How it actually works

A research run starts from a goal — a name to look into, or a natural-language request — and is driven by a single orchestrator through nine agent families in a fixed order: Supervisory, Discovery, Prospect Intelligence, Relationship Intelligence, Qualification, Strategy, Knowledge Integrity, Operations, and Application. Fifty-one agents are registered across those families, each with a defined mission, an autonomy level, and (for most of them) an explicit human boundary it cannot cross on its own.

Progress is checkpointed after every family, not just at the end — if a run is interrupted, it resumes from the next incomplete family instead of starting over. If any agent comes back needing a person's judgment, the run pauses in a resumable state and waits for that review to be resolved rather than skipping ahead or failing outright.

The last step before a run completes is always dossier synthesis — a dedicated agent turns everything gathered into a single narrative dossier with facts and inferences explicitly separated, evidence citations, confidence scores, and recommended next actions. Once that's done, qualified prospects are automatically handed to AutoApply's queue.

Inputs and outputs

INPUTS
  • A goal: a specific name to research, or a natural-language request
  • Your organization’s own request profiles, for matching once qualified
  • A token and dollar budget for the run, enforced agent by agent
  • Permitted sources: open web, public records, news, 990s, SEC EDGAR, and more
OUTPUTS
  • A narrative dossier with facts, inferences, citations, and confidence scores
  • Mission-affinity, funding-eligibility, capacity/propensity, and timing scores
  • A relationship graph with warm-introduction paths and strength ratings
  • A cultivation plan and, once qualified, a ranked entry in AutoApply’s queue

Where a person is in the loop

No agent in this pipeline contacts a prospect. Every one of them researches, scores, or drafts a recommendation for a person to act on — approving actual outreach is its own explicit review type, separate from every other kind of check below.

Human review queue. Identity linkage, capacity determinations, policy exceptions, autonomy increases, high-impact actions, and outreach approval all route to a queue a person has to resolve. An agent that hits one of these doesn’t skip it or fail the run — it pauses in a resumable state until a person decides.

An agent watches the agents. A dedicated Autonomy Governor continuously monitors every active run for policy violations and can terminate one immediately — and by design it cannot approve its own authority increases or policy exceptions; only a human decision can resolve those.

Every action is logged. An append-only audit trail records every agent and human action, and a policy engine attaches an allow, deny, or require-human decision to each one — so any recommendation the system produces can be traced back to exactly what it saw and why it decided that.

Quantified results

We don’t have a published research-accuracy or dollars-identified figure for Prospect Intelligence yet — the rollout that would generate real numbers hasn’t started. We’d rather show you an honest “pending” than a number we backed into. This section will be replaced with real pilot data once we have it.

What it actually connects to

RESEARCH SOURCES

Tracked in a source registry as permitted, restricted, or prohibited before any agent can query them, with a rate limit and a stored, hashed snapshot behind every claim.

  • Open web, public records, and news
  • IRS Form 990 filings and SEC EDGAR
  • Corporate and foundation information, licensed databases, permitted APIs
DOWNSTREAM
  • AutoApply — a completed, qualified research run is handed straight to AutoApply’s submission queue
  • Outbound webhooks — organizations already configured for AutoApply’s queue-populated event are notified the same way

Security and reliability

Access is org-scoped end to end — every table carries an organization id, and the rollout flag itself is evaluated per organization, so one team’s access never leaks into another’s. If the flag service is unreachable or a flag is unset, the feature fails closed and stays hidden rather than opening up by accident. Every claim in a dossier is tied to a stored source snapshot with a content hash, so evidence can be checked against what was actually retrieved, not just trusted. Cost budgets can be set at the organization, agent, or single-run level, with an optional hard stop. For the platform-wide security and governance model, see the Trust and Governance page.

Read the Trust and Governance page

Customer story

COMING SOON

We don’t have a published customer story for Prospect Intelligence yet — no organization has used it in production, because the rollout hasn’t started. Once a pilot organization has run it against a real cultivation cycle and agreed to be named, their story will go here — not a composite or hypothetical example.

FAQ

Is Prospect Intelligence available on my account today?
Not yet for most organizations. It's gated behind an organization-level rollout flag that defaults to off, and the platform's own canary rollout hasn't started — every teammate at a given org sees the same on/off state, so it's never partially on for one person and off for another. If you want in before the wider rollout, ask us — see the call to action below.
Does it contact donors or prospects on its own?
No. Every agent in the pipeline researches, scores, and drafts a recommended strategy for staff to review — none of them send an email, place a call, or otherwise reach a prospect. Approving actual outreach is its own dedicated human-review type, separate from every other kind of review the system files.
Where does the evidence actually come from?
Open web sources, public records, news, nonprofit filings (IRS Form 990), SEC EDGAR, corporate and foundation information, licensed databases, and permitted APIs — each one tracked in a source registry as permitted, restricted, or prohibited before any agent is allowed to query it. Every claim in a dossier carries its source, a retrieval date, and one of several verification levels — verified fact, corroborated fact, single-source fact, reasoned inference, or estimate — so a guess is never presented as a confirmed fact.
What happens when two sources disagree?
The disagreement is recorded as a contradiction, not silently resolved by picking one side. A dedicated agent investigates and either resolves it in favor of one source, marks both as stale, or leaves it open for a person to decide — the dossier reflects whichever of those is actually true, rather than presenting a single confident number.
How does this connect to AutoApply?
Once a research run finishes, qualified prospects are automatically matched against your organization's own request profiles and handed to AutoApply's submission queue for the governed application process described on the AutoApply page. Nothing about that hand-off skips AutoApply's own eligibility, risk, and rate checks.
FREE, NO ACCOUNT REQUIRED
Not sure which funders to research first?

Run the free Funding Potential Scan first — a short, no-signup check of the kind of funding your organization is likely to qualify for.

Try the free Funding Potential Scan

Build My Prospect Map

Prospect Intelligence is in controlled rollout, not yet open to every account. Talk to us about early access, or see the governed pipeline it feeds once a prospect is qualified.

Build My Prospect MapSee what happens after a prospect qualifies