Built with manufacturers, equipment OEMs and universities
Meallions OS connects the entire food manufacturing ecosystem in one governed workflow—bringing together product requirements, formulation knowledge, process simulation, equipment behavior, verification, and production data.
It turns what teams learn in research and on the line into better decisions for the next recipe, the next run, and every connected production site. Experts stay in control while AI handles the repeatable work of moving from intent to production-ready action.
Shared knowledge base of verified research, ingredients, machinery, and connected-site production.
Every project and site strengthens the platform.
Meallions OS moves repeatable R&D work into a subscription platform, so experts spend production line time verifying a better starting point.
Traditional
2–4 weeks
Digital twin
2–5 hours
Cost impact
Up to 95% lower cost
Start with a ranked, sourced hypothesis.
No blank-page research.
Traditional
1–8 weeks
Digital twin
1–2 days
Cost impact
Up to 92% lower cost
Rank candidates against technical, nutrition and cost constraints.
Iterate with BOM and nutrition together.
Traditional
2–6 weeks
Digital twin
1–3 hours
Cost impact
Up to 97% lower cost
Evaluate twin-screw behavior before scale-up.
Resolve more before committing line time.
Traditional
4–9 weeks
Digital twin
2–4 days
Cost impact
Up to 50% lower cost
Start the line from evaluated parameters.
Confirm instead of discovering.
Traditional
1–3 weeks
Digital twin
1–2 hours
Cost impact
Up to 83% lower cost
Check the approved result against its targets.
Decision history stays connected.
Cost reductions are measured against a conventional development programme for the same product on the same equipment. The savings above 90% apply to research, formulation, simulation and release documentation, where verified knowledge and digital-twin runs replace repeated physical trials. The physical production run is capped near 50%: material, energy, labour and line time remain real costs, and the saving comes from fewer failed runs, less scrapped material and shorter commissioning. Actual figures are confirmed per pilot against the customer's own baseline.
General AI can help explain a problem. Meallions OS helps teams work through specific food-manufacturing decisions by connecting verified evidence, source priority, technical constraints, equipment context, process methodology, and production feedback.
Move from research through digital validation and line trials to controlled scale-up.
Time to scale
Optimize raw-material cost, energy, yield, and waste while protecting quality.
Cost/kg and energy/kg
Respond earlier to ingredient variability and emerging process drift.
Yield and variation
Maintain human approvals, confidence thresholds, overrides, and audit-ready records.
Deviations and overrides
Every project and production site improves shared recipes, models, and operating decisions.
Ecosystem improvement and ramp time
Every answer is grounded in sources we've checked, and you can see them.
A four-stage funnel: indexed articles are screened, each remaining source is checked, and the result is the Verified Sources knowledge base.
The full corpus collected from domain publications, journals and trusted outlets.
N articles
Duplicates, low-quality and off-topic material removed.
N articles
Each source is assessed for authority, recency and consistency with other sources.
N sources
The curated knowledge base the platform answers from.
N sources
Each source gets a reliability rating based on the authority of the publisher, its recency, and its agreement with other Verified Sources. Higher-rated sources carry more weight in answers.
Every key statement in an answer comes with an inline citation. Clicking it opens the original article via a direct link, so you can verify the claim yourself.
Example answer
Higher barrel moisture typically lowers expansion in extruded cereals[1].
[1] Source title placeholder
Verified · HighPublisher name · Publication date
Open sourcePrepared knowledge corpus
Meallions: Curated, domain-specific corpus
General-purpose AI: Broad web training data, not curated
Source verification
Meallions: Every source checked and rated, cited in answers
General-purpose AI: Sources usually not verified or shown
Domain specialization
Meallions: Built for food manufacturing and food extrusion
General-purpose AI: General knowledge across all topics