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.

All comparisons

Decision Intel vs IBM watsonx.governance

IBM audits the model; Decision Intel audits the human reasoning.

Decision Intel vs IBM watsonx.governance

IBM audits the model; Decision Intel audits the human reasoning.

What IBM watsonx.governance does well

IBM watsonx.governance audits AI model behaviour: lineage tracking, fairness metrics, drift detection, model risk management. Massive Q1 2026 product updates explicitly targeting EU AI Act readiness for high-risk AI systems. Bundled with the broader IBM enterprise stack, a strong incumbency advantage at Fortune 500 procurement.

Where Decision Intel is different

IBM audits AI MODELS. Decision Intel audits HUMAN REASONING — the chain of analysis a human author produced before a recommendation reached the committee. The strategic-memo authorship is human (or AI-assisted by the human); watsonx has no detector for cognitive bias in human reasoning, no Recognition-Rigor Framework, and no public reference-class corpus. The two products are not substitutes; they are complementary layers of governance.

Axis	Decision Intel	IBM watsonx.governance
AI model lineage + drift detection	Out of scope (we audit humans, not models)	Core product capability
Cognitive bias detection on HUMAN-authored memos	22-bias canonical taxonomy with academic citations	Not in product
Recognition-Rigor Framework (Kahneman + Klein arbitrated)	Protected IP moat; ten paper-application detectors shipped	Not in product
EU AI Act Article 14 (human oversight) artefact	DPR maps directly onto Art. 14 record-keeping by design	Model-side AI Act compliance, not human-oversight artefact
Historical reference-class library	143 corporate decisions across 12 industries	Model benchmark suites, not decision-outcome library
Pan-African / EM regulatory mapping	NDPR, CBN, WAEMU, POPIA, SARB and seven more	US-and-EU centric registry
Solo-buyer onramp without enterprise procurement cycle	Free tier and £249/mo individual tier; sign-up in minutes	Enterprise-only, procurement-led, multi-month sales cycle

FAQ

Do I need both IBM watsonx.governance and Decision Intel?

If you run AI MODELS in production AND author strategic memos that go to committee, yes — they audit different surfaces. IBM audits the model; Decision Intel audits the human reasoning. EU AI Act Article 14 (human oversight) is the artefact that joins them.

Will IBM not eventually add human-reasoning audit?

They could. The differentiator is not the category claim — it is the depth of the academic anchor (Kahneman & Klein 2009, ten R²F detectors), the 22-bias taxonomy with stable IDs, the 143-case reference library, and Pan-African regulatory coverage. Replicating those takes years; we built the moat first.

Other comparisons

vs Cloverpop

Cloverpop logs decisions; Decision Intel audits them.

vs Aera Technology

Aera automates supply-chain decisions; Decision Intel audits strategic ones.

vs Palantir

Palantir is data-platform infrastructure; Decision Intel is the reasoning-audit layer above it.

vs ChatGPT (or general-purpose LLMs)

ChatGPT is a general-purpose LLM; Decision Intel is a purpose-built reasoning-audit engine.

vs McKinsey (or any strategy consultancy)

A McKinsey engagement is a one-time deliverable; Decision Intel is always-on infrastructure.

Run the audit on a real memo.

The category claim is the H1. The category proof is the artefact. Paste a strategic memo and see the audit run end-to-end, free.

Run the live demo

IBM audits the model; Decision Intel audits the human reasoning.

What IBM watsonx.governance does well

Where Decision Intel is different

Axis	Decision Intel	IBM watsonx.governance
AI model lineage + drift detection	Out of scope (we audit humans, not models)	Core product capability
Cognitive bias detection on HUMAN-authored memos	22-bias canonical taxonomy with academic citations	Not in product
Recognition-Rigor Framework (Kahneman + Klein arbitrated)	Protected IP moat; ten paper-application detectors shipped	Not in product
EU AI Act Article 14 (human oversight) artefact	DPR maps directly onto Art. 14 record-keeping by design	Model-side AI Act compliance, not human-oversight artefact
Historical reference-class library	143 corporate decisions across 12 industries	Model benchmark suites, not decision-outcome library
Pan-African / EM regulatory mapping	NDPR, CBN, WAEMU, POPIA, SARB and seven more	US-and-EU centric registry
Solo-buyer onramp without enterprise procurement cycle	Free tier and £249/mo individual tier; sign-up in minutes	Enterprise-only, procurement-led, multi-month sales cycle

FAQ

Do I need both IBM watsonx.governance and Decision Intel?

Will IBM not eventually add human-reasoning audit?