Skip to main content

Your diligence AI is confident.That’s the problem.

Your AI said the ARR was clean, the waterfall worked, and the add-backs were one-time. One of those is wrong. Often more than one. Confidence isn’t accuracy.

Three AI models. Adversarial analysis. Every conclusion challenged before you see it.

Deliberation in progressRound 2 of 4
Strategic Analyst
Conviction78%
Risk Analyst
Conviction80%
Research Analyst
Conviction82%
Synthesis · Converging

Trusted Infrastructure

Dedicated Tenant IsolationPatent PendingSOC 2 Type II Certified HostingYour Data Never Trains Our Models

What Single-Model AI Misses

The numbers inside it are wrong.

Three things that change whether a deal is investable.

We ran the same deals through a single frontier model and through Delibera. The single model produced solid-looking IC prep memos. Delibera caught the things that actually changed the investment thesis.

Case 01

The ARR Restatement

The single model accepted $14.2M ARR at face value. Delibera's research agent pulled 10-Qs and reclassified revenue quality. Adjusted ARR: $11.8M. That moves entry multiple from 10x to 12.5x — a number no IC would approve without renegotiating price.

Case 02

The Waterfall Math

The single model computed IRR at 13% and called it “thin.” Delibera ran the actual waterfall at specific exit values. At $250M — the base case — the B-1 uncapped participating preferred makes MOIC 0.89x. Not thin. Capital destructive.

Case 03

The EBITDA Normalization

A $20M EBITDA services business — classic mid-market buyout at 7x. The single model accepted management’s normalized EBITDA. Delibera cross-checked the add-backs: $2.5M of “one-time” expenses recurred three years running, $800K in related-party lease adjustments were understated, and revenue from a terminated Q4 customer was included in TTM. Real normalized EBITDA: $16.7M. Effective multiple: 8.4x, not 7x.

Across SaaS, growth equity, and traditional buyouts, the pattern is the same. Single-model AI produces confident analysis that misses the specific errors that change investability. Delibera doesn’t replace your QoE or legal DD — it makes sure you don’t walk into IC with a false sense of security before the real work starts.

See the full methodology

How It Works

Not one AI with a second opinion. Three AIs that actually disagree.

Delibera runs adversarial deliberation between independent models, with gap-driven research and mandatory dissent. You see the argument, not just the answer.

01

Three Independent Models Analyze

Strategic, Risk, and Research analysts — three AI models from different providers — analyze your matter simultaneously. Each one has a distinct role.

02

Adversarial Deliberation

Models challenge each other's reasoning through multiple structured rounds. Dissent is required. Blind spots, conflicts, and failure modes surface before you see them.

03

Verified Synthesis & Audit Trail

Conclusions are verified against real sources — case law, SEC filings, peer-reviewed literature — with a timestamped record of every challenge and resolution.

Input

“Review this target’s ARR quality and flag any quarters where restatement risk justifies a walk-away.”

Deliberation
Converging
StrategicARR at $12M but 34% from three customers.
RiskCustomer concentration breaches diligence threshold.
ResearchThree 10-Qs show restatement in Q3. Walk.
Synthesis

Walk-away recommended. Three agents converged (confidence 91%). Audit trail attached: CourtListener citations, SEC 10-Q references, and each agent’s dissent preserved.

Benchmark Results

Independently tested. The numbers.

Phare Hallucination Benchmark · 791 adversarial samples

Higher is better

DeliberaThis system
0.0%

3 models · adversarial deliberation

Claude Opus 4.6
0.0%

Anthropic frontier

GPT-5.4
0.0%

OpenAI frontier

0%

vs. Next-Best Model

Fewer hallucinations than Claude Opus 4.6 — the closest frontier comparison.

0+

Across Suites

Adversarial samples tested across Phare and internal suites. Every result reproducible.

The Hard Conversation

Every analysis includes what you might not want to hear.

Uncomfortable trade-offs. Reasons your preferred path might fail. Blind spots in how you framed the question.

The Question

Should we approve the Alpha Partners bid at 10x TTM?

Strategic
78% confidenceApprove

Headline numbers support it — $14.2M ARR, 22% YoY, gross margin 74%. Multiple defensible against 2024 comps.

Risk
82% confidenceCounter

The deck is clean; the filings aren't. Three 10-Qs show Q3 revenue restated in the last 18 months. That's a pattern, not a one-off.

Research
88% confidenceWalk away

Top-3 customer concentration is 34% of ARR — above your stated 25% walk-away threshold. MSA renewal on the largest is Q2 next year.

SynthesisWalk away

Restatement pattern plus customer concentration above the stated threshold. At 10x TTM this is not the deal you modeled — it's a deal with two structural risks the memo didn't price in.

“Better to confront it in private than discover it in court — or across the deal table.”

Junior analysts don’t push back on MDs. Associates don’t push back on partners.

Someone needs to say the thing no one wants to say. Delibera does.

Bring a deal.We’ll show you what your AI missed.

30-minute live briefing. Bring a real deal — or try our sample analysis. Keep the output.

Typical briefing · 30 minutes · live deliberation demo · you keep the output

Private Equity

Mid-market and growth equity teams catching ARR restatements, waterfall errors, and normalization issues before IC

Corporate Development

Buy-and-build platforms and strategic acquirers running lean on DD resources

Investment Banks

M&A advisory teams producing IC memos that survive the partner who didn’t read the deck

M&A Counsel

Transactional attorneys verifying citations and flagging interpretation risk before close