Know what your tests actually prove.
QI connects requirements, test results, configurations, calibration records and deviations into a source-grounded evidence record. It identifies gaps and leaves every conclusion to your engineers.
Evidence reconstruction for hardware qualification. Prototype, synthetic demo data.
QI Desktop · synthetic demo data
Start with qualification.
Qualification evidence is scattered across requirements, procedures, test data, configurations, calibration records, findings, deviations, and reports. QI reconstructs those relationships into a traceable evidence chain for engineering review.
Requirements
Spec database
Procedures
QMS / PDF
Test data
Chamber export
Calibration
Certificate file
Configuration
PLM revision
Findings
Test log
NCRs
Quality system
Reports
Shared drive
Qualification produces all of this — but rarely in one place. QI reconstructs the chain for engineering review.
Evidence chain · TVAC Payload A
Step 5 / 9Finding
Flags a limit violation or engineering observation.
Findings anchor to a time region, channel, and acceptance criterion. They are the entry point for evidence reconstruction.
Qualification campaigns produce bounded, reviewable evidence. The relationships are real — but distributed across systems. QI is where we prove the model.
- ·One campaign, one evidence chain, one review workflow.
- ·Gaps and missing links surfaced explicitly.
- ·Foundation for broader engineering context.
Engineering context, not isolated documents.
Engineering knowledge on aerospace, space and defense hardware programs is distributed across systems, files, tools, teams, and years of history. The goal isn't another chatbot that reads a document. The goal is an engineering environment that understands how the pieces relate.
Knowledge lives in separate systems, folders, and teams. QI reconstructs relationships across bounded campaign exports — starting with qualification evidence, building toward engineering context.
Context graph · conceptual model
Telemetry ↔ Findings
A limit violation is not an isolated alert — it is an observation anchored to a time region, channel, and acceptance criterion.
Campaign example
Peak 69.9 °C against a 65 °C qualification upper limit.
In Pilot-1 today
Findings link to data regions, limits, and requirement references.
Live traceability
Same relationships, rendered from a synthetic demo campaign.
The conceptual graph above maps how engineering knowledge should connect. Below is the Pilot-1 prototype reconstructing traceability for the TVAC Payload A qualification campaign — select a finding, inspect nodes, open gaps.
Qualification intelligence, today.
Pilot-1 capabilities in the validation prototype. No claims beyond what the product demonstrates.
Evidence reconstruction
Connect requirements, procedures, runs, findings and dispositions.
Configuration awareness
Track the hardware revision, test configuration and relevant changes.
Source-grounded investigation
Every important result points back to source evidence.
Missing evidence
Identify gaps, unresolved questions and broken evidence chains.
Human review
AI prepares the investigation. Engineers retain decision authority.
Open the TVAC campaign to see traceability, evidence chains, and review state in the prototype, which runs on synthetic demo data.
Built around the data boundaries of regulated hardware programs.
Engineering data doesn't always belong in a public cloud. QI is designed around customer-controlled workflows — from approved campaign exports to private environments and read-only access to authoritative systems.
Customer Systems
Approved Data Boundary
QI
Engineering Context
AI Investigation
Human Review
Your authoritative engineering systems remain authoritative.
QI is designed to work within the boundaries aerospace, space and defense organizations already use — NDA, customer-controlled upload, bounded campaign access, read-only analysis, and defined retention. Architectural awareness, not a compliance certification.
AI investigates. Engineers decide.
Source-grounded
Results trace back to engineering evidence.
Configuration-aware
Understand revisions, test articles and engineering context.
Auditable
Preserve provenance and review state.
Human-controlled
AI prepares investigations and recommendations. Engineering authority stays with people.
QI is not a qualification authority. Evidence for human review only.
Works across the systems you already use.
QI is not trying to replace the systems that already hold authoritative engineering data. It connects the context between them.
QI
Unified Engineering Context
Designed to connect across systems · not a claim of live integrations with every system listed
Company direction
From qualification intelligence to engineering intelligence.
QI is the first wedge. We are building toward an AI-native engineering environment — governed by evidence, not hype. What exists today is the qualification prototype; what follows is the direction we are building toward.
Reconstruct the evidence.
Connect engineering relationships.
Understand the system across tools and artifacts.
Preserve what the organization has learned.
Investigate, prepare and eventually execute engineering workflows with human approval.
An AI-native environment for the engineering lifecycle.
Help us build the engineering environment hardware programs have been missing.
We are working with aerospace, space and defense engineers, test engineers, AIT teams, and qualification leads to understand how evidence is created, connected, reviewed, and reused.
Or email us directly at ceo@ilconcetto.org
Test Qualification Intelligence on one completed campaign
We can start with a completed historical campaign. No production system integration is required initially. The goal is to measure whether the workflow reduces reconstruction effort and improves evidence traceability.
Drafts save in this browser. Submit appends your interest to our discovery sheet.