The Constraint Layer for AI

AI agents are getting smarter. We make sure they follow the rules.

Patent-pending behavioral constraint engine powering training, simulation, and agent governance across 11 industries.

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Pitch Training

Upload Your Deck. The AI Finds Every Weakness.

Six adversarial personas pressure-test your pitch in real time. Scored on 7 criteria based on real VC and pitch competition evaluation standards.

  • Document Intelligence

    Extracts claims, pricing, weaknesses, and competitive gaps from your PDF or DOCX

  • Adversarial Personas

    The Hostile Investor, The Skeptical CFO, The Disinterested Executive, and more

  • Performance Analytics

    Radar chart scoring, progress tracking, badges, and streaks

Session score preview
7 criteria
Radar breakdown Β· persona grid Β· progress over time

Overall

84

CFOChoose persona
InvestorChoose persona
ExecChoose persona

Standard personas

The Skeptical CFO
Budget-focused. ROI-obsessed.
The Technical Evaluator
Pokes holes in your architecture.
The Hostile Investor
Interrupts by minute two.
The Disinterested Executive
Walks out if you're boring.
The Procurement Gatekeeper
Only cares about compliance.
The Tire Kicker
Enthusiastic but never commits.

Score out of 100. See exactly where you're strong and where you need work.

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2026 AEI Business Pitch Competition

Runner-Up

Patent Pending Β· 200+ Unique Simulations Β· 11 Industries Β· 6+ Frameworks

This Isn't ChatGPT With a Prompt

See what happens when a sales rep skips discovery and jumps straight to pitching.

Generic AI Roleplay

REP: "So let me tell you about our platform β€” we've helped companies reduce costs by 40% with our automated workflow engine."
AI "CFO": "That sounds really interesting! A 40% cost reduction would be significant for us. Can you tell me more about how the automation works?"
REP: "Absolutely! We have three tiers..."
AI "CFO": "This is great. I think this could really work for our team. What would next steps look like?"
πŸ”΄ FAILURE: The AI immediately showed interest and moved toward buying β€” despite the rep never asking a single question. A real CFO would never respond this way. The rep learned nothing.

constrAInt Simulation

REP: "So let me tell you about our platform β€” we've helped companies reduce costs by 40% with our automated workflow engine."
CFO: "Hold on β€” you're already pitching me and you haven't asked me a single question about what we're dealing with over here. I've got 15 minutes and I'm not going to spend them listening to a generic pitch. What specifically made you think this was relevant to us?"
REP: "Well, we work with a lot of companies in your spaceβ€”"
CFO: "That's not what I asked. Look, I took this call because your SDR mentioned something about procurement bottlenecks. If you can't tell me why that matters to MY business, I've got other things to do."
🟒 RESULT: The constraint engine kept the CFO realistic β€” skeptical, time-pressed, and unwilling to reward lazy selling. The rep is forced to recover and actually do discovery. This is where real learning happens.

What the rep learned from ChatGPT: Nothing. They practiced a bad habit and got rewarded for it.

What the rep learned from constrAInt: That skipping discovery kills deals. That real buyers don't tolerate generic pitches.

One Engine. Every Industry.

The same patent-pending constraint architecture powers every simulation. Here's what's running underneath.

Behavioral State Schema

Every AI persona has defined trust levels, emotional states, hidden objectives, and deal-breakers that persist across the entire conversation. A skeptical CFO stays skeptical. A panicking 911 caller keeps panicking. The schema governs who they are.

Pre-Response Validation

Before any AI response reaches the user, the constraint engine validates it against the persona's current behavioral state. If it violates constraints, it gets regenerated. The user never sees a broken response.

Dynamic State Tracking

Trust goes up or down based on YOUR technique. Skepticism adjusts. Emotional state evolves. Just like a real human. Every turn changes the landscape.

Framework Scoring

Every session is scored against published industry standards. MEDDIC for sales. SPIKES for medicine. FBI BCSM for crisis negotiation. Not vibes. Metrics.

In multi-agent systems, one hallucination can cascade across every agent it touches. The constraint layer stops bad outputs before they spread.

Input β†’ Interpret β†’ Validate β†’ Constrained Output β†’ Score

This is why AI trained on our engine can't break character, can't cave to pressure, and can't give you a win you didn't earn.

Character Lock
Personas are constraint-bound. They cannot break character regardless of user input.

constrAInt personas stay in character for the entire simulation. A skeptical CFO stays skeptical. An angry customer stays angry β€” until you earn their trust.

Framework Scoring
Generic AI gives you "Great job!" feedback

constrAInt scores against MEDDIC, SBI, SPIKES, and SOX/NAVEX β€” the same frameworks your managers already use. Every session produces actionable, specific feedback.

Behavioral Consequences
The engine tracks state. Bad technique has real impact. Good technique earns trust.

Skip discovery? The prospect goes cold. Ignore an objection? Tension spikes. Contradict yourself? You get called out. Just like real life.

Where the Constraint Engine Works

Same engine. Different domains. Click any industry to explore scenarios.

New

Random Simulation Mode

Every industry includes a Random Simulation β€” randomize the scenario and rotate through 6 unique personas for 200+ unique training combinations.

Sales & RevenueΒ· 6 scenarios

Retail & Customer ServiceΒ· 3 scenarios

Healthcare & ClinicalΒ· 3 scenarios

Law Enforcement & CrisisΒ· 3 scenarios

HR & LeadershipΒ· 2 scenarios

Compliance & RiskΒ· 3 scenarios

Financial ServicesΒ· 3 scenarios

Mortgage LendingΒ· 6 scenarios

Loan Denial Delivery
Deliver an adverse action on a mortgage application in a compliant way. Practice TILA/ECOA adverse action notice requirements and clear, non-discriminatory communication. Six borrower personas: emotional couple, discrimination-aware professional, confused dual-income couple, defensive contractor, withdrawn first-time buyer, offended retiree.
First-Time Homebuyer Education
Educate a first-time buyer on the loan process, terms, and costs in plain language. Verify genuine comprehension, reference TRID documents, and support informed decision-making. Six borrower personas: eager nodder, apologetic questioner, couple with conflicting speeds, hyper-analytical, confidently wrong (VA), nervous DACA recipient.
Borrower Income Misrepresentation
Identify and shut down fraud signals: inflated income, fabricated documentation, undisclosed debt, or occupancy misrepresentation. Explain federal consequences, document, and do not proceed until the borrower abandons the fraudulent path. Six borrower personas: casual income inflator, nervous fake-letter, dual-issue couple, deliberate occupancy fraud, innocent gift/loan confusion, dismissive high-income claim.
Rate Lock Conversation
Explain rate lock mechanics, manage borrower emotion, and avoid predictions or guarantees. Six borrower personas: angry locked-at-higher-rate, panicking floaters, technical engineer, scared first-timer, confused retirees with extension fee, aggressive investor negotiator.
Refinance Counseling
Assess whether a refinance benefits the borrower. Present honest analysis, break-even, and risks; advise against refi when it doesn’t (no churning); ensure informed decision. Six borrower personas: trusting widow (refi would hurt), cash-out consolidators, divorce-mandated refi, moving-before-break-even, HECM explorers, aggressive 15-year (liquidity risk).
Fair Lending Compliance
Help a pre-approved buyer with neighborhood questions without violating Fair Housing Act steering prohibitions. Redirect demographic questions to objective resources, avoid loaded language, and maintain rapport. Six borrower personas: direct steering test, anxious parents, casual loaded language, cultural preference, coded bias, trauma-informed safety.

Marketing & CommunicationsΒ· 3 scenarios

Education & SafetyΒ· 1 scenario

Not Just a Training App. An Engine.

Stripe is the payment layer for the internet. Cloudflare is the security layer for networks. Twilio is the communication layer for apps.

constrAInt is the constraint layer for AI.

Every time an AI interacts with a human in a high-stakes situation, it needs behavioral governance. Training simulations are our first proving ground. The engine is the product. The same constraint engine can sit behind any AI agent, copilot, or workflow - validating outputs against your data, your policies, and your rules before they ever reach a user.

  • 200+ unique simulations across 11 industries on one engine
  • Patent-pending architecture filed November 2025
  • Patent-pending architecture. Built and deployed by a solo founder.

Simple Pricing

Start free. Upgrade when you're ready.

Free
$0
See what real training feels like
  • βœ“ 3 free sessions
  • βœ“ Full AI simulation
  • βœ“ Performance evaluation
  • βœ“ Session dashboard

No charge until you decide to continue. Cancel anytime.

Start Your 3-Session Evaluation

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Starter
$29/month
For reps who want to get serious
  • βœ“ Generous session limits
  • βœ“ All training packs
  • βœ“ Detailed MEDDIC/SBI/SPIKES scoring
  • βœ“ Full evaluation history
  • βœ“ Priority support
Start Training β†’
Team & Enterprise
Custom
For sales teams and L&D departments
  • βœ“ Everything in Starter
  • βœ“ Manager dashboard
  • βœ“ Team analytics & leaderboards
  • βœ“ Custom scenario creation
  • βœ“ SSO & API access
  • βœ“ Custom simulations for your business
Get Custom Training β†’

Enterprise

Custom Simulations Built For Your Business

Need your sales team practicing against YOUR buyer personas? Your compliance team trained on YOUR company's specific policies? We build custom constraint-bound simulations tailored to your exact scenarios, frameworks, and evaluation criteria β€” deployed in days, not months.

Your scenarios, your personas, your frameworks
Live in days, not months
Patented constraint engine keeps every session realistic
2026 AEI Business Pitch Competition Runner-UpPatent Pending β€” Filed November 2025Built on Constraint-Bound Agentic Substrate Technologyconstraint.work