From specification
to certainty.
Three steps · One prediction engine · No more surprise blockers
[ Active failure modes ]
04 signals- Steep learning curve
- Supply chain scan
- Manufacturing bottlenecks
- Regulatory mapping
One structured roadmap. No surprises.
Time
Compress your lab-to-market timeline by eliminating avoidable iteration cycles. Know what to build before you build it.
Money
No unforeseen rework costs. No late supplier pivots. No certification redesigns. The savings compound at every stage.
The right suppliers
Pre-validated EU supplier network matched to your material spec, quality control requirements, and lead time constraints — before you need them.
Regulatory clarity
Your certification pathway mapped from day one. Dossier preparation runs in parallel with R&D, not after it.
Team alignment
R&D, manufacturing, procurement, and regulatory — working from one shared, structured roadmap instead of four separate timelines.
Focused R&D
Not everything needs trial and error. Realise identifies where model-driven prediction can replace experimental cycles — and where focused R&D still needs to happen. No wasted runs.
12 months or 24. Your choice.
WITH REALISE
Month 1
Specs submitted to Realise
✓ Supply chain risks flagged · Pivot suggested
Month 2–3
Design locked with pre-validated supplier network
✓ Quality control requirements confirmed upfront
Month 4–6
Prototype built with industrialisable parameters
✓ Certification pathway mapped in parallel
Month 7–9
Pilot production run
✓ ISO 22734 / ATEX alignment pre-confirmed
Month 10–12
Demonstration & commercial launch
✓ No unforeseen costs · No surprises
RESULT: 12 months · Budget maintained · Launch on schedule
No black box. A clear sequence.
- 01
· Describe your challenge
You describe your scale-up challenge in the form below.
- 02
· Engine runs
We run your project through the Realise prediction engine.
- 03
· Structured risk report
You receive a structured risk report: supply chain, manufacturing, and regulatory blockers ranked by severity, with pivot suggestions.
- 04
· Working session
One working session with the Realise team to walk through the findings.
Feed it your design.
Upload technical specifications — CAD files, simulation outputs, material choices, performance targets. Realise reads the language engineers actually use.
- ·CAD ingest
- ·Simulation parse
- ·Spec normalisation
The engine thinks.
Hybrid AI — a symbolic knowledge graph encoding industrial constraints, coupled with ML trained on historical deeptech project data — maps your design against 10,000+ known failure patterns.
- ·Supply chain graph
- ·Manufacturing constraints
- ·Regulatory matrix
Recommendations you can act on.
Not a black box. Not 'consult an expert'. Specific, explainable alerts with impact estimates — so engineers can make the call, not guess.
- ·Explainable alerts
- ·Impact estimates
- ·Pivot suggestions
Explainable alerts.
⚠ Supply chain risk — High
Nickel-90% spec creates 8-month sourcing constraint. Your timeline: 3 months. Suggested pivot: Nickel-72% alloy, 2-week lead time, −3% performance impact.
⚠ Manufacturing — Medium
Electrode coating uniformity at ±2μm validated at lab scale. Industrial deposition processes achieve ±8μm. Recommend tolerance review before tooling investment.
✓ Regulatory — Clear
Regulatory clearance preincluded in industrialisation strategy.
Explainable by design.
We didn't build a black box. Realise uses symbolic AI — rules and relationships engineers can read and challenge — combined with machine learning for pattern detection. Every recommendation shows its reasoning. Because engineers don't trust what they can't interrogate.
lower carbon footprint than LLM alternatives
fewer emissions per query vs GPT-4
black-box outputs
[ Carbon footprint per query · log-scale truth ]
Bars shown at minimum visible width — actual Realise footprint is ~500,000× smaller than the LLM baseline.
Common questions.
- Q.01
- Q.02
- Q.03
- Q.04
- Q.05
Is my engineering data safe?
Yes. Realise does not retain, train on, or share your project data. All analysis is scoped to your session and discarded after your scale-up scenarios are generated.
What file formats do you accept?
PDF specs, COMSOL/Ansys simulation exports, Excel material tables, and plain-text design documents. CAD files are on the roadmap.
How long does an analysis take?
For a standard electrolyzer or battery stack submission: 48–72 hours for the full risk report during the pilot phase.
How is Realise different from a consultant?
A consultant takes 6 weeks and costs €30K–€100K. Realise returns explainable, structured risk flags in 48 hours — before you've committed to a design freeze.
What's the price?
The Q3 2026 pilot is free for the 3 selected teams. Paid tiers (Pro, Premium, Power) open after the pilot.