Your best deals share hidden DNA.
We find it.
Most sales teams target accounts based on firmographics and gut feel. Recursive Intelligence analyzes your actual deal outcomes to discover the compound signals that predict which companies will buy – before your competitors even know to call.
The problem
70% of your pipeline
is wasted motion.
What teams do today
- •Target based on firmographics and gut feel
- •Treat every account as equally likely to close
- •Run the same playbook against every prospect
What they miss
- •The compound signals hiding in 50+ data fields
- •Second-order patterns no human could spot
- •The specific combination of attributes that predict a win
What Recursive Intelligence reveals
- •Which accounts have 10x higher close probability – and why
- •Hidden DNA shared by your best deals
- •The signals that degrade and the ones that strengthen over time
How it works
Four steps. Compounding intelligence.
Learn from your wins
We analyze every closed deal – won and lost – to discover what actually drives your revenue. Not what you think drives it. What the data proves drives it.
Discover compound signals
Individual signals are noise. Compound signals are signal. When a company shows three specific attributes simultaneously, close rates jump 5-10x. We find those combinations automatically.
Score every account
Every company in your TAM gets a score based on how many compound signals they exhibit right now. Your reps focus on the accounts most likely to close, this quarter.
Get smarter every deal
Each outcome validates or refines the model. Signals that stop predicting are deprecated. New signals are discovered. Your intelligence gets sharper with every deal you close.
Compound signals
Your ICP is wrong.
Let your data prove it.
These are not rules you configure. They are patterns the system discovers from your own deal history. Every customer's model is unique because every customer's winning patterns are unique.
lift
Leadership transition + expanding engineering + competitor stack
Organization is modernizing with budget and mandate to act.
lift
Recent funding + rapid sales hiring + no rev ops tool
Scaling pain without infrastructure. They need help now.
lift
Industry peer just bought + competitor contract renewal approaching
Competitive urgency aligned with budget timing.
lift
Champion response time < 2 hours + 3+ stakeholders engaged
High-intent buying group with internal momentum.
Example signals shown for illustration. Actual compound signals are discovered uniquely for each customer and are never shared between organizations.
Results
Trained on your wins.
Validated on your outcomes.
40%
Reduction in wasted pipeline
3x
Improvement in forecast accuracy
60%
Faster high-intent account identification
5-10x
Close rate lift on compound signals
Self-improving
Gets smarter every quarter.
Automatically.
Most scoring models are static. You set rules, they decay. Recursive Intelligence validates its own predictions against real outcomes and adjusts continuously. Signals that stop working are deprecated. New signals are discovered. The model improves with every deal.
Prediction tracking
Every score the system assigns is tracked against the actual outcome. You see exactly how accurate the model is – and how fast it is improving.
Signal deprecation
Markets change. Signals that predicted wins last year may not predict wins this year. The system detects degrading signals and removes them automatically.
Signal discovery
When the model gets a prediction wrong, it analyzes what it missed. New candidate signals are generated from the gap between prediction and reality.
Causal validation
Correlation is not causation. The system validates that compound signals are genuinely causal, not coincidental. Only verified signals drive scores.
Use cases
Intelligence for every motion.
Account Prioritization
Stop treating all accounts equally. Score your entire TAM by compound signal density and focus reps on the accounts with 5-10x higher close probability.
ICP Refinement
Your ICP was defined in a conference room. Recursive Intelligence defines it from data. Discover which attributes actually predict revenue – not which ones feel right.
Forecast Accuracy
Replace gut-feel forecasting with signal-based prediction. Know which deals will close this quarter based on the compound signals present today.
Territory Planning
Assign territories by signal density, not just geography or company size. Every rep gets an equal probability-weighted book of business.
Content Targeting
Know which content resonates with accounts exhibiting specific compound signals. Align marketing spend with the accounts most likely to convert.
Pipeline Review
In every pipeline review, see which deals have the compound signals that predict closed-won – and which are wasting your team's time.
Platform integration
Recursive Intelligence makes every Adrata feature smarter.
Compound signals flow into buyer group mapping, deal intelligence, and pipeline analytics – turning structural data into predictive understanding.
Company Intelligence
Deal Intelligence
Pipeline Analytics
The companies that win the next decade will not be the ones with the most reps or the biggest marketing budgets. They will be the ones that understand – at a mathematical level – why their best deals close and which accounts are next.
Recursive Intelligence is how you get there.