L1
Big Five & DISC psychographic profiling
How they process information, make decisions, and act under stress.
How Raven AI Works
Seven layers of behavioral intelligence. One living simulation.
The machine extracts. The scientist interprets. The counterpart gets built — not from an archetype, from the actual person.
0Existing platforms simulating a named individual
7Behavioral extraction layers in the Raven's Edge stack
18Competitors analyzed — none combine profiling with simulation
The Engine
How LLMs extract psychology from language.
Language is the residue of thought. LLMs can read the residue. Raven AI turns that reading into a behavioural signature.
- 01
Raw Text Inputs
Speeches, emails, interviews, filings — any language the counterpart has produced.
- 02
Linguistic Patterns
Argument structure, hedging density, framing choices, authority signals.
- 03
Pragmatic Inference
What the language does — not just what it says. Implied positions, deflections, tells.
- 04
Psychological Extraction
Big Five, DISC, influence susceptibility, decision heuristics — surfaced from language, not self-report.
- 05
Confidence Scoring
Every dimension rated by source quality and signal strength. HIGH / MODERATE / INFERRED.
The Seven Layers
Behavioral frameworks encoded at intake.
Each framework is a lens on the counterpart. Together they form the Raven's Edge Intelligence Stack — validated behavioral science, not a personality quiz.
L2
Cialdini's six principles of influence
Which persuasion levers this person responds to — and which they resist.
L3
BATNA & negotiation behavioral modeling
Anchoring style, walk-away behavior, pressure response.
L4
Kahneman & Tversky prospect theory
Framing and anchoring sensitivity — how gains and losses register.
L5
Schwartz values theory
What they optimize for when the stakes are real.
L6
Communication science & language signature analysis
Framing preferences, tells, and the language they use when the guard drops.
L7
Behavioral economic biases and heuristics
Cognitive shortcuts and decision patterns — where their judgment can be anticipated.
How We Build the Counterpart
Eight data inputs. External and internal signal, weighted together.
Every input is sourced, weighted, and confidence-scored. The counterpart model is only as good as the signal — so we make the signal visible.
External & Public
What the world can see.
- Published interviews, keynotes & authored content
- Social media & public posts
- Conference speeches & panel transcripts
- Regulatory filings & public testimony
- Press profiles, analyst reports & third-party coverage
- Role norms, organizational culture & industry pattern inference
Internal & Intimate
What only you can bring.
- Psychologically-calibrated stakeholder interviews (AI-aggregated & extracted)
- Client-provided data: emails and/or recorded conversations
The White Glove Offering
The machine extracts. The scientist interprets.
LLM extraction is necessary. It is not sufficient. Raw linguistic signals require a trained human mind to weigh them — one that understands not just what the patterns are, but what they mean for this person, in this context, against these stakes.
Phase One
LLM Extraction Output
The machine does what machines do best.
- Raw linguistic pattern signals
- Flagged framework candidates
- Cross-source signal aggregation
- Preliminary confidence estimates
- Identified data gaps & ambiguities
Ingestion, pattern matching, and scale.
Phase Two
Behavioral Science Synthesis
A trained scientist reviews, challenges, and validates.
- PhD-level framework adjudication
- Competing signal arbitration
- Contextual validity assessment
- Paralinguistic nuance weighting
- Confidence gate calibration
Applying judgment no model can replicate.
Phase Three
Validated Behavioral Intelligence
The output is not a report. It's an intelligence product.
- Defensible, sourced dossier dimensions
- Confidence ratings with justification
- Remediation map for data gaps
- Practitioner-ready strategic guidance
- Simulation-ready persona calibration
Built to hold up under pressure.
One Integrated Engagement
Intelligence and simulation — delivered together.
Every client goes to the table ready.
Intelligence Dossier
The counterpart profile.
Built to hold up under pressure.
- Behavioral Profile
- Big Five & DISC — how they process, decide, and act.
- Values & Decision Drivers
- What they optimize for when the stakes are real.
- Communication Style
- Language signatures, framing preferences, and tells.
- Negotiation Tendencies
- Anchoring style, walk-away behavior, pressure response.
- Contextual Motivation
- What's at stake for them in this specific deal.
- Recommendations Layer
- Dos, don'ts, and watch-outs specific to this person.
Live Simulation
Practice against the actual person.
Before you walk in the room.
- In-Character Responses
- Persona reacts calibrated to documented psychology.
- Offer & Framing Testing
- Run multiple approaches — see what lands before it matters.
- Adaptive Coaching
- Meta-level guidance without breaking the persona's character.
- Pressure Scenario Probes
- Push the limits of what the counterpart will accept or resist.
- Session Intelligence Log
- Every session deepens the model and sharpens the strategy.
- Real-Time Recommendations
- What's landing, what's backfiring, and what to adjust.
The Platform: Now and Next
In active development.
Here is where we are — and where we are building.
Today
What’s Live Today.
- Full 7-layer behavioral extraction pipeline operational
- Source Confidence Gating Framework live across all dimensions
- Dossier delivery in structured, client-ready format
- AI persona simulation live (Mode A: AI simulates counterpart)
- Real-time coaching mode (Mode B: advisor-in-loop)
- 3-agent delivery workflow: Analysis, Structuring, Simulation
- 33-prompt Prompt Registry implemented and deployed
- First pilot client validated — data and feedback in hand
Active Beta · The Vision
The Platform We’re Building.
- Rich UI Dashboard
- Full client-facing simulation environment — session controls, persona history, and confidence scoring visualized in real time.
- Emotional Trigger Analytics
- Live indicators of which emotional registers are activated in the persona — mapped to behavioral science frameworks and session trajectory.
- Persona Learning Log
- What the persona is learning about the client across sessions: perceptions, pressure points, and how the counterpart's model of you is evolving.
- Predictive Behavioral Indicators
- Forward projections: concession likelihood, resistance thresholds, and next-move predictions based on cumulative session intelligence.
- Evergreen Data Layer
- Live data feeds updating persona intelligence as public signals evolve — earnings calls, press statements, leadership changes — keeping the model current.
Let’s talk.
Raven AI is in active development with a defined architecture, commercial model, and clear market.
We’re building the category of individual counterpart behavioral intelligence — and we’re the only ones in it.