Work the accounts that actually convert
Every visitor and lead scored with explainable propensity, at-risk deals flagged before they slip, and a pipeline forecast with confidence bands the board stops second-guessing.
The week ends before the selling starts
Reps inherit stale lists and manual research while deals slip in silence. The agents take the grind.
The static list wastes hours
Reps work a list sorted by download date, not by who is actually buying, and burn their week on accounts that were never going to close.
Busywork eats selling time
Research, enrichment, first-touch email, CRM hygiene · the work that has to happen but isn't selling.
Deals slip silently
By the time a deal shows up as at-risk in the forecast, the champion has already gone quiet.
Saved-view archaeology
Finding the right list means rebuilding the same filter for the tenth time instead of just asking for it.
Propensity turns the list into a queue
| Account | Score | Stage | Owner |
|---|---|---|---|
| OpenAI | 94 | Decision | K. Liu |
| Anthropic | 91 | Intent | M. Patel |
| Cursor | 89 | Consideration | K. Liu |
Every account in your TAM scored on fit, intent, and engagement, then bucketed High / Medium / Low. High Fit gets the AE's calendar; Low Fit gets nurture. The rep opens a queue sorted by who is buying now.
- Propensity scoring on ICP, intent, and behavior
- High / Medium / Low tiers with projected pipeline
- Scores write back to Salesforce and HubSpot
- Round-robin or rule-based ownership
Reps sell. Agents do the rest
| Lead | Company | Signal | Score |
|---|---|---|---|
| Anika Shah | Truevo | 3 pricing visits | 91 |
| Marcus Holt | Pomelo | Demo + 2 docs | 88 |
| Priya Iyer | Vyne | Webinar + pricing | 86 |
SDR, enrichment, research, and revival agents draft and send as your reps, then write the activity back to the CRM. The grunt work happens overnight; the rep walks in to a warmed list.
- Per-rep identities · agents send as your team
- Account research briefs before every call
- Inactive-lead revival on a dormancy trigger
- Every touch logged back to Salesforce
Risk surfaced while you can still act
| Account | Amount | Prob. | Risk |
|---|---|---|---|
| Cursor | $240K | 82% | Champion AWOL |
| OpenAI | $148K | 68% | No exec mtg |
| Anthropic | $120K | 71% | Stage stale |
Key Deals and Early-Stage Risk agents read the forecast surface daily, flag the deals that carry the number, and ping the owner in Slack the moment a risk signal appears · a stalled stage, a missing exec meeting, a quiet champion.
- High-value × high-probability lens, refreshed daily
- Risk signal library · 10+ patterns
- Owner pinged in Slack on a new flag
- Forecast contribution shown per deal
The agents Sales runs
Each owns one job and acts on the same context layer · proposed, approved, reversible.
SDR Agent
Drafts and sends first-touch as the rep, writing back to Salesforce.
Key Deals
Surfaces the deals that carry the forecast and pings the owner daily.
Early-Stage Deals at Risk
Flags slipping deals before the close date moves.
Account Research
Builds a brief on demand from the web and LinkedIn before the call.
Built on the two cores: the Context Layer and the Agents
RevSure turned 31,000 anonymous companies into a working list, sorted by who was actually buying. Our SDRs went from a 4% reply rate on a static list to 14% on the prioritized one.
Elizabeth Villarreal
Demand Gen Lead · Abnormal AI
Why RevSure for Sales
Scored on one context layer
Every lead ranked on the same resolved truth, so the queue reflects who is really buying.
Agents send as your reps
Per-rep identities mean the outreach is yours · the agent just does the typing.
Reversible by construction
Every agent action is proposed, approved, and one click from rollback.
Work the few accounts that actually close
Implementation included. The first prioritized queue lands in week one.