IMPACT
AI that holds up in audit. Here is the evidence.
Industrialized rituals in production, with measured, attributed results.
Rituals in production
No case study for this family yet.
Rituals in production
Banking & investment · public sector
Mapping critical import dependencies
From weeks of manual analysis to minutes, with evidence and lineage for the regulator. Deployed on-premise, in production.
1–2 months → min. · Analysis cycle time
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Automotive industry
Supplier compliance and requirements extraction
Automatic extraction of requirements from specifications, matching to internal procedures, native Audit Pack.
~€150,000 / year · Savings on manual analysis
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B2B distribution
Catalog classification and three-level scoring
~21,000 products classified per year with green / amber / red scoring. Merchandisers validate in Human in the loop.
82% · Precision on first proposal
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Innovation & financing
Deep-tech knowledge graph
Extraction of a ~10,000-node graph from thousands of PDF pages to map deep-tech emergence paths.
~10,000 nodes · Knowledge graph extracted
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Insurance
Certified actuarial and asset-management reports
Three rituals on one Core: actuarial report, asset management, management control. Generated comments, sourced and auditable via Audit Pack.
3 rituals · One Core, one Audit Pack
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What is measured is attributed. What is projected is a contractual commitment, not an observed result.
Case studies
What it changes, client by client.
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Bpifrance
250 cases a year now processed in under 48 hours instead of several weeks, with ~19 days saved per quarter per analyst—1.2 FTE shifted onto strategic analysis.
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Groupama GAN Vie
Management control produces its numeric commentary automatically, and actuarial reports ship in hours instead of weeks of manual drafting.
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Givaudan
Millions of consumer opinions read and objectified at scale: fine-fragrance creation rests on a sourced sensory readout.
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L'Oréal
Consumer feedback—texture, scent, feel—is read at scale and turned into actionable signals.
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Nestlé
Media campaigns are tested on synthetic consumers before go-live: marketing trade-offs rest on quantified evidence.
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Manutan
~21,000 supplier products reclassified automatically each year into the right sub-families, with a three-colour scorecard.
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EDF
Thousands of 3D EPR mock-up logs analysed automatically. Anomalies predicted before an incident; decisions signed and auditable.
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Carrefour
One photo of a dish is enough. A vision engine identifies each ingredient, builds the full basket and triggers the order.
What changes
What these results mean for you.
In every case the starting point is the same: a critical process that depends on human expertise, takes too long, and whose compliance nobody can prove after the fact.
What Nexa changes is not the process itself: it is what the process produces. Each run yields a traceable result, justified by its sources, validated by a human expert and ready for audit. The cycle shortens, regulatory risk falls, and teams focus on the decision rather than on checking.
ROI is not only hours saved. It is risk avoided, audits passed without reconstruction, and knowledge capital that compounds with every use.
Audit response time: minutes, not weeks. The Audit Pack is produced on every run; it is not rebuilt when the regulator asks.
Experts arbitrate; they no longer correct. Human validation is about the decision, not about checking what the AI assembled.
Every use enriches the organisation. Validated prompts, optimal configurations and compliance policies accumulate in a memory that belongs to you.
Your business ritual has the same potential.
Evidence is not our constraint. It is our product.
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