Launch first in medtech.
The AI workspace that turns your design decisions into a living regulatory record. Development, accelerated — up to 30 months sooner*, rigour intact.
FDA 510(k) · PMA · De Novo · EU MDR · EU IVDR
Live workspace preview: asked whether the glucose sensor can be read every 30 seconds, MANKAIND answers that one minute is the floor because the battery requirement fails below it — then recommends tightening the five-minute spec to one minute and drafts the change for review: the requirement revised, a new dosing-latency requirement added, the rationale written, the hazard re-scored, tests flagged. The record stays unsigned until a human approves: the document is in review, awaiting Quality.
Impact
Rigour that stays coherent.
Your device reaches patients up to 30 months sooner*.
When the record builds with every engineering decision, the submission path clears in hours* instead of months. The saved span comes back as runway, revenue and treated patients.
One change updates the whole record.
A design decision is never isolated. It re-scores hazards, flags tests, revises the DHF and rebuilds traceability — automatically. The record stays true to the device, so nothing is orphaned and nothing is missed.
Audit-ready is your resting state.
Because the record is built as you engineer, it is already signed, traced and current. An audit becomes a reading exercise; a submission becomes an export.
The record is the product.
* Timeline: company model, medical device programmes. “Hours” measured on synthetic programmes — ask for the methodology in your demo.
How it works
One decision in. A signed record out.
01
You decide
Make the engineering call the way you always do. The moment it exists, it's a captured record — attributed, timestamped, already part of the programme.
02
The AI propagates
One change fans out across the graph — risk file, V&V plan, traceability, documentation. Updated in minutes, with citations attached.
03
You sign. It files.
Review the draft, sign it, done. The record lands in the eQMS — audit-ready, mapped to your submission, yours.
An AI co-engineer with the whole programme in mind.
Agentic AI over one connected graph — every requirement, hazard, test, decision, and the standards that govern them. That's how it catches the misclassification you didn't ask about, flags the test your change just invalidated, and answers design questions with citations at midnight.
The operating loops
Three loops. One system.
One AI workspace: agentic AI, product lifecycle management (PLM) and the electronic quality management system (eQMS) in a single system — the living design record and the signed quality record, on the same loop as your team. Where stitched-together tools hand off at every seam, one system carries the work straight through — and the programme stays coherent as the device grows.
Your team engineers. Your documentation keeps pace.
The platform
One workspace. Three accelerations.
Complexity that stays coherent as your device grows. Decisions made with the whole programme in context. Documentation that builds itself — signed, traced, submission-ready. Four capabilities on one loop deliver them.
Assistant
An expert in engineering, compliance — and your project's full context.
Answers drawn from the connected programme graph — your requirements, hazards, tests, and standards — so every decision is made with the whole system in mind.
Workspace
The workspace is the system of record.
Design decisions flow into compliant, traceable records as you work. The documentation is not separate from engineering — it is how the complexity of your device stays coherent.
Vault
Quality events stay part of the same record.
CAPAs, NCRs, complaints and audits are connected to the engineering decisions that caused them — one quality system, one design history, one coherent story.
Workflows
The whole methodology keeps itself coherent on every change.
Multi-model AI agents run the engineering cascade — each change propagates through risk, traceability and documentation so the record stays true to the device.
In command
The AI does the work.
The judgment stays yours.
Every entry to your record passes through you — that control is built into the system, not bolted on. And MANKAIND itself arrives ready to qualify: the platform is yours to validate, with the evidence in hand.
The validation package, included
Qualify MANKAIND under ISO 13485 §4.1.6 — intended use, validation summary, and the Part 11 evidence your quality team needs to sign off the tool itself.
For your quality team.
Compliance & security
Built for regulated engineering.
The certifications your procurement team will ask for — and the controls behind them.
Certifications
SOC 2 Type II
Security controls, verified over time.
Audit in progress — completing 2026ISO 27001
Information security management.
Audit in progress — completing 2026ISO 42001
AI management system, governed.
Audit in progress — completing 202621 CFR Part 11
E-signature and audit-trail controls for FDA-regulated work — validation package provided for your assessment.
GDPR
EU data protection controls for your engineering data, with a DPA.
Security controls
- Human in the loop
- Write operations require human approval — with an audit trail of who approved what, and when.
- Encrypted, logged
- AES-256 encryption protects your engineering data at rest, and every access is logged.
- Your data stays yours
- Zero retention by model providers — your engineering data is never used for model training.
- Leave with everything
- Full export in standard formats at any time: design history, traceability, risk files.
Use cases
Your device. Your pathway. One engineering motion.
From Class I hardware to SaMD and combination products — one platform, every regulatory market. Find the moment that sounds like your programme.
Design · Medical Devices
Your neurostimulator works. Your record does not.
A 15-person team, 47 DHF gaps at design review, and the RA consultant can't come until next month. The engineering record is falling behind the device.
On MANKAIND
The DHF grows out of the engineering work itself — design reviews open with a current, coherent file that reflects every decision made so far.
Read the medical devices use case →Design · Software as Medical Device
You changed a design input on your AI diagnostic
You retrained the model. Now IEC 62304 documentation, SOUP items, safety classification, and V&V all need reassessment. The impact assessment takes two weeks in spreadsheets.
On MANKAIND
The change propagates in minutes — safety classification, SOUP items and V&V scope re-assessed across the graph, every impacted item flagged for your review.
Read the SaMD use case →Verification · In Vitro Diagnostics
Your IVD assay failed validation. The pharma partner is waiting.
Between-lab repeatability failed acceptance criteria. Performance evaluation report invalid. Risk analysis needs revisiting. And the pharma partner's clinical trial timeline depends on your assay.
On MANKAIND
The failure traces through the graph — impacted acceptance criteria, risk entries and the performance evaluation report are flagged and re-drafted while your lab reruns the study.
Read the IVD use case →Submission · EU Market Access
Your Notified Body audit is in 12 weeks
You have FDA clearance but the EU MDR technical documentation looks nothing like your DHF. GSPR checklist, clinical evaluation, post-market surveillance—all from scratch.
On MANKAIND
The EU MDR file is generated from the same design graph as your DHF — GSPR mapping, clinical evaluation structure and the PMS plan drafted from evidence you already hold.
Read the EU MDR use case →Submission · FDA Submissions
Your 510(k) is next quarter. Your DHF has gaps.
34 orphaned requirements in your traceability matrix. Verification tests that reference renumbered specs. The predicate comparison table is half-empty. Eight weeks of rework ahead.
On MANKAIND
The traceability matrix is generated from the design graph — orphans surface the day they appear, and the predicate table fills from your own records.
Read the 510(k) use case →Post-market · Quality Management
A surgeon just reported a malfunction
Root cause analysis needs the original design decisions, manufacturing records, and risk analysis. They live in four different systems. The engineer who made those decisions left eight months ago.
On MANKAIND
The malfunction report opens onto the full history — original decisions, risk analysis and manufacturing records, linked on one graph and answerable in one search.
Read the CAPA use case →One engineering motion