How is sensitive data protected?

All documents are encrypted with AES-256-GCM at rest and TLS 1.2+ in transit. A GDPR anonymization layer removes PII before any AI processing. Hosted on Vercel + Supabase (both SOC 2 Type II); Decision Intel’s own product-level audit is targeted for Q4 2026.

How long does integration take?

Less than 30 minutes. Upload documents directly, connect via OAuth for Slack, or use our REST API for bulk processing.

How does outcome tracking work?

Outcomes are detected automatically from follow-up documents, Slack messages, and web intelligence. You confirm with one click. Each reported outcome makes your future analyses more accurate.

How is Decision Intel different from ChatGPT or a general AI assistant?

ChatGPT gives one opinion from one model: ungoverned, untraceable, unaudited. Decision Intel is the reasoning audit platform. Most tools audit your data; we audit your reasoning — and catch the fatal blind spots in strategic memos before the committee does. It measures the noise in your reasoning the same way Kahneman did in the insurance underwriter study, simulates an AI boardroom of CEO, CFO, and board personas, runs what-if interventions against a 143-case public reference library, and compounds every confirmed outcome back into a calibrated Decision Quality Index your audit committee can defend. Not a chatbot; a reasoning audit, checkable from memo to outcome.

Which cognitive biases caused U.S. Federal Government (CMS)'s failure?

5 bias patterns are documented in this case, led by Planning Fallacy. The full set: Planning Fallacy, Authority Bias, Groupthink, Overconfidence Bias, Sunk Cost Fallacy. Each is mapped to Decision Intel's 22-bias R²F taxonomy with stable IDs and academic citations.

What is Decision Intel's reasoning audit?

Decision Intel runs a 12-node Recognition-Rigor Framework (R²F) pipeline on strategic memos, detecting cognitive biases from a 22-bias canonical taxonomy and producing a Decision Quality Index (DQI) score. The audit produces a hashed, tamper-evident Decision Provenance Record (DPR) suitable for audit-committee review.

All case studies

FailureGovernment2013

U.S. Federal Government (CMS)

Healthcare.gov Launch Disaster

Estimated impact: $1.7B+ wasted; massive political damage; delayed healthcare coverage for millions

F30

Decision Quality Index (simulated)

Critical · 5 biases detected, 2 toxic combinations

The launch of Healthcare.gov on October 1, 2013 was a catastrophic technical failure. The site crashed almost immediately, with only 6 people successfully enrolling on day one out of 250,000 who attempted. The project cost over $1.7 billion, involved 55 contractors with no single integrator, and ignored repeated warnings from engineers that the system was not ready. Planning fallacy led to unrealistic timelines, authority bias caused political leaders to overrule technical concerns, and groupthink among officials prevented honest assessment of readiness.

Decision context

Whether to launch the healthcare exchange website on the mandated October 1 deadline despite internal testing showing critical failures, or delay the launch and face political consequences.

Decision anatomy

Monetary stakes

Very high

Dissent suppressed

Time pressure

Present

Unanimous consensus

Decision participants

Dissent encouraged

External advisors

Iterative process

Red = risk factor present · Green = protective factor present

Deep hindsight-stripped analysis coming soon. This case is part of our ongoing backfill to reconstruct what the platform would have flagged at decision time. The summary and bias profile below are drawn from primary sources.

In Their Own Words

Primary-source quotes

“Let me say directly to these Americans: you deserve better. I apologize.”

Secretary Kathleen Sebelius, Congressional testimony · October 30, 2013

Biases present in the decision

★Planning Fallacy

critical

Authority Bias

high

Groupthink

high

Overconfidence Bias

high

Sunk Cost Fallacy

high

★ Primary driver · Severity estimated from bias type and decision outcome

3D Decision Knowledge Graph

U.S. Federal Government (CMS) · 5 biases, 2 toxic combinations

Drag to rotate · Scroll to zoom · Click to explore

Decision

Critical

High

Medium

Toxic

Bias Intensity Profile

Severity × confidence across 5 detected biases

Toxic combinations

!The Blind Sprint

Compound cognitive failure pattern identified in this decision.

!The Yes Committee

Compound cognitive failure pattern identified in this decision.

Reference class base rates

Across all 143 curated case studies in our library:

89%

base failure rate

-0%

partial / mixed

11%

base success rate

■ Failure■ Partial■ Success

Lessons learned

Planning fallacy in government IT projects is endemic — the GAO found that 94% of large federal IT projects are over budget, behind schedule, or both.
Authority bias caused political leadership to override technical warnings about system readiness, treating the launch date as immovable.
The lack of a single system integrator across 55 contractors created diffusion of responsibility — no one owned the overall outcome.

Source: GAO Report GAO-14-694 (2014); Office of Inspector General Report OEI-06-14-00350; U.S. House Committee on Energy and Commerce hearing transcripts (October 2013) (Post Mortem)

Pilot slots available

We caught these patterns in U.S. Federal Government (CMS)'s own record — before the outcome.

See the full bias auditwe ran — no login, no card. Then run the same 60-second audit on your own next memo.

See a live audit · no login Audit your own memo

Or leave your email, we'll run a strategic memo of your choosing and send the readout within a business day.

Audit your own decision

Workflows that fire on decisions like U.S. Federal Government (CMS)’s

The same Recognition-Rigor Framework that documents this case audits memos in the same shape — before the outcome forces the lesson.

For CSOs and Heads of Strategic Planning

Strategic memo audit

Audit a strategic memo for cognitive bias and forecast errors in 60 seconds — before the board sees it.

Audit a strategic memo

For any high-stakes decision, before commitment

Decision pre-mortem

Run a structured pre-mortem before the decision is final — surface failure modes the room cannot see from the inside.

Run a pre-mortem

For CSOs and CEOs presenting to a board

Board deck pre-presentation audit

Audit a board deck before the presentation — predict the toughest questions the room will ask.

Audit your board deck

See all 6 workflows for the full audit-tool surface.

Related cases in Government

Failure2013

US Centers for Medicare & Medicaid Services (CMS)

Healthcare.gov Launch Failure

Failure2020

Flughafen Berlin Brandenburg GmbH

Berlin Brandenburg Airport Delays

Partial failure2001

US Department of Defense / Lockheed Martin

F-35 Joint Strike Fighter Cost Overruns

Failure2013

UK Department for Work and Pensions

UK Universal Credit IT Disaster

Lessons learned

Planning fallacy in government IT projects is endemic — the GAO found that 94% of large federal IT projects are over budget, behind schedule, or both.

Authority bias caused political leadership to override technical warnings about system readiness, treating the launch date as immovable.

The lack of a single system integrator across 55 contractors created diffusion of responsibility — no one owned the overall outcome.