Auditable AI expert platform for high-stakes industrial decisions.
QognyX captures expert know-how, turns it into versioned decision logic, and produces operational deliverables: checklists, SOP drafts, investigations, and executive-ready reports — with traceability from source to answer.
Most AI tools generate text. QognyX is built for environments where teams need control, validation, and evidence — not “best guesses”.
Produces structured decision steps — not just answers — so teams can review, approve, and reuse them.
Turns conversations, procedures, and documentation into reusable knowledge capsules with clear scope and version history.
Keeps an auditable chain: sources used, checks performed, and what changed over time — so outputs are defensible.
Want to see QognyX on a real workflow?
A simple, end-to-end flow designed for real operations.
Bring your SOPs, manuals, incidents, and SME notes into a structured knowledge base.
Convert know-how into reusable decision logic: conditions, steps, thresholds, exceptions.
Apply scope controls and evidence linking so outputs can be reviewed and trusted.
Generate artifacts teams use: checklists, SOP drafts, investigations, executive summaries.
Clear deliverables, ready to use — from operators to executives.
Checklists, troubleshooting trees, SOP drafts, RCA investigations, shift handover notes.
Recommendations anchored to your documents with traceability for review and audits.
Structured reports: decision context, assumptions, risk, and action plan.
Want to see QognyX on a real workflow?
Start small, prove outcomes, then scale. We scope a single workflow and define success metrics upfront.
1 site · 1 workflow · 1 “owner” · clear boundaries (what QognyX should and should not answer).
Selected SOPs + incident reports + SME review sessions to build the first knowledge capsules.
Track acceptance rate, time-to-answer, consistency, and reduction of rework/escalations where applicable.
Operational artifacts delivered weekly: checklists, SOP drafts, investigations, and summaries.
Most AI tools generate plausible text. QognyX is engineered for high-stakes industrial environments where control, evidence, and long-term value matter more than speed alone.
Unlike conventional copilots that reset after each session, QognyX builds a versioned, reusable Memory Vault. Every insight, procedure, and decision becomes a knowledge capsule that improves over time — never lost, never starting from zero.
Other AIs deliver black-box answers. QognyX produces traceable, step-by-step decision logic with clear evidence linking, source references, validation gates, and full auditability — so your teams can review, approve, and defend every output.
While most tools stop at chat, QognyX captures deep domain expertise and turns it into concrete, ready-to-use assets: checklists, SOP drafts, root-cause investigations, and executive reports — grounded in your own documents and know-how.
Generic copilots optimize for conversational flow. QognyX is designed for regulated, high-liability industrial contexts: scoped knowledge, change tracking, defensible outputs, and no hallucinations without evidence. Control stays with your experts, not the model.
Early signals from pilot-style workflows — shared as anonymized projections for transparency.
“QognyX reduced our time-to-RCA by structuring our existing incident notes into reusable decision steps and evidence-linked outputs.”
— Reliability Engineer, Manufacturing (anonymized)
“The value isn’t the chat — it’s the validation gates and the ability to reuse the same approved logic across shifts.”
— Operations Lead, Asset-Intensive Site (anonymized)
“Having traceable sources + decision logs made approvals faster. People trust what they can review.”
— Quality / Compliance, Industrial Company (anonymized)
Based on early pilot projections — these are directional indicators, not final customer case studies. Replace with measured pilot metrics once available.
Realistic outcomes based on early pilot simulations and industrial benchmarks. These projections illustrate how QognyX performs in high-stakes operational environments. No client data is used — transparency is part of our operating model.
“By structuring incident records into traceable decision steps, QognyX reduced investigation cycles by an estimated 30–40%, while maintaining full auditability.”
— Projected outcome, Reliability Engineering (Aerospace / Manufacturing)
“Capturing expert knowledge into reusable logic reduced SOP drafting from weeks to days, with every step linked to verified sources.”
— Projected outcome, Operations Management (Industrial Sites)
“Evidence-backed summaries reduced reporting time while improving leadership confidence in operational decisions.”
— Projected outcome, Executive Operations (Regulated Industry)
Based on early pilot projections and public industry benchmarks (e.g. McKinsey Operations & Reliability reports). These figures are validated and refined during customer pilots.
Built for teams who need control, not magic.