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 Pacific Gas and Electric's collapse?

5 bias patterns are documented in this case, led by Status Quo Bias. The full set: Status Quo Bias, Cognitive Misering, Loss Aversion, Anchoring Bias, Planning 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

Catastrophic failureEnergy2018

Pacific Gas and Electric

PG&E Camp Fire Liability

Estimated impact: $13.5B

F17

Decision Quality Index (simulated)

Critical · 5 biases detected, 1 toxic combinations

PG&E's failure to maintain aging transmission infrastructure caused the Camp Fire, the deadliest and most destructive wildfire in California history. The fire killed 85 people and destroyed 18,804 structures. PG&E had deferred maintenance and vegetation management for years despite knowing its equipment posed wildfire risks.

Decision context

Whether to invest in replacing aging transmission lines and aggressive vegetation management in high-risk wildfire zones, or to continue deferring maintenance to reduce operating costs.

Decision anatomy

Monetary stakes

Very high

Dissent suppressed

Time pressure

None

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.

Biases present in the decision

★Status Quo Bias

critical

Cognitive Misering

medium

Loss Aversion

medium

Anchoring Bias

high

Planning Fallacy

medium

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

3D Decision Knowledge Graph

Pacific Gas and Electric · 5 biases, 1 toxic combination

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

!Status Quo Lock

Loss aversion combined with status quo bias makes even clearly beneficial change feel impossible.

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

Status quo bias in infrastructure maintenance means deferred spending accumulates as hidden risk until catastrophic failure.
Cognitive misering in risk assessments leads utilities to treat wildfire risk as a low-probability event rather than updating for climate change.
Loss aversion around short-term earnings prevents the capital investment needed to prevent long-term catastrophic losses.

Source: Cal Fire Investigation Report on Camp Fire (2019); PG&E Chapter 11 filing (2019) (Case Study)

Pilot slots available

We caught these patterns in Pacific Gas and Electric'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 Pacific Gas and Electric’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.

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All case studies

Catastrophic failureEnergy2018

Pacific Gas and Electric

PG&E Camp Fire Liability

Estimated impact: $13.5B

F17

Decision Quality Index (simulated)

Critical · 5 biases detected, 1 toxic combinations

Decision context

Whether to invest in replacing aging transmission lines and aggressive vegetation management in high-risk wildfire zones, or to continue deferring maintenance to reduce operating costs.

Decision anatomy

Monetary stakes

Very high

Dissent suppressed

Time pressure

None

Unanimous consensus

Decision participants

Dissent encouraged

External advisors

Iterative process

Red = risk factor present · Green = protective factor present

Biases present in the decision

★Status Quo Bias

critical

Cognitive Misering

medium

Loss Aversion

medium

Anchoring Bias

high

Planning Fallacy

medium

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

3D Decision Knowledge Graph

Pacific Gas and Electric · 5 biases, 1 toxic combination

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

!Status Quo Lock

Loss aversion combined with status quo bias makes even clearly beneficial change feel impossible.

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

Status quo bias in infrastructure maintenance means deferred spending accumulates as hidden risk until catastrophic failure.
Cognitive misering in risk assessments leads utilities to treat wildfire risk as a low-probability event rather than updating for climate change.
Loss aversion around short-term earnings prevents the capital investment needed to prevent long-term catastrophic losses.

Source: Cal Fire Investigation Report on Camp Fire (2019); PG&E Chapter 11 filing (2019) (Case Study)

Pilot slots available