Product Delivery
Track exactly how much your AI generates each month in euros.
We manage your Data and AI initiatives like business products: with users, KPIs, and traceable ROI. Not like tech projects that disappear once delivered.
+150 companies supported
— 5/5 on Google
Benefits / Impacts
Benefits
Tangible results for your organization, measurable within the first weeks of engagement.
01
AI models that solve business problems
Each model we develop meets a defined business objective: reduce a cost, accelerate a process, improve a prediction. No model for the sake of modeling.
02
Orchestrated and controlled AI agents
Your GenAI agents are not working freewheeling. We put in place safeguards, monitoring and validation circuits that guarantee reliable and controlled responses.
03
POC to production transition included
We don't ship a notebook. We deliver an industrialized system, integrated into your business tools, deployed in production and monitored. The POC is only a step, not the deliverable.
04
Leveraging your proprietary data
The real value of GenAI in business is when it works on your data, not on generic knowledge. We connect LLMs to your information assets for results specific to your context.
05
Enhanced team competence
Our Data Scientists work with yours, not for them. The transfer of skills is integrated so that your team gains autonomy on new techniques.
Chapters
Our expertise
The skills and expertise we leverage to deliver results in this area.
Tools / Partnerships
How we apply this expertise
We work with all market-leading frameworks and platforms. Technology choices are dictated by your use case, confidentiality constraints, and existing infrastructure, never by tool preference.
Amazon Web Services
Google Cloud
Azure
Apache Airflow
Power BI
Amazon Web Services
Google Cloud
Azure
Apache Airflow
Power BI
Amazon Web Services
Google Cloud
Azure
Apache Airflow
Project types
What we deliver
Actionable deliverables, not just recommendations. Here are the types of engagements we offer for this expertise.
01
Production-ready predictive model
From scoping to production: development, validation, and deployment of a machine learning model integrated into your business processes. Customer scoring, demand forecasting, fraud detection, logistics optimization.
02
RAG System on Proprietary Data
Connecting an LLM to your internal document base to allow your teams to query your data in natural language. Technical documents, knowledge base, contracts, publications.
03
Business AI Agent
Design and deployment of an autonomous agent that executes complex workflows: automated email processing, document analysis, report generation, decision support.
04
Computer Vision System
Development and deployment of computer vision models: visual quality control, medical image analysis, object recognition, anomaly detection on production lines.
Business Cases
They industrialized Data Science and GenAI with us
We don't deliver POCs. We deliver working systems with a measurable impact on our clients' businesses.
Vos questions, nos réponses
Toutes les réponses pour comprendre notre approche, notre façon de travailler et ce que vous pouvez attendre de notre collaboration.
What is Applied GenAI?
A Data Product is a data or AI solution managed as a business product, with identified users, measured KPIs and a traceable ROI. Diametral manages your data initiatives as sustainable products rather than one-shot projects, which guarantees their adoption and long-term value.
What is a RAG system?
The Data Product Manager acts as a bridge between tech and business teams: he defines the vision of the product, prioritizes the roadmap, measures the value generated and arbitrates changes. Diametral integrates senior Data Product Managers into its squads or trains your own to create this role that is still rare in most groups.
Comment mesurer le ROI d'un projet IA ?
Industrializing an AI agent means moving it beyond demo mode to become a supervised, measured, and governed system. Diametral frames each agent with safeguards (content filters, human validation for critical actions, comprehensive logs) and measures the value generated month after month to ensure it remains an asset and not a black box.
What is the difference between a POC and industrialized AI?
A POC demonstrates feasibility within a small scope; an industrialized AI runs in production with SLAs, monitoring, and integration with business tools. Diametral avoids the 'eternal POC' syndrome by defining production readiness criteria from the outset: target volume, integration with the information system (IS), governance, and expected ROI.
How to avoid GenAI hallucinations?
Avoiding hallucinations relies on four practices: anchoring responses in your documents via RAG, validating outputs with business rules, implementing human oversight for sensitive cases, and tracing each response for audit. Diametral integrates these layers by default in every enterprise GenAI deployment.
contact
Got an AI use case in mind? Let's build it together.
Describe your problem. A Diametral Senior Data Scientist will assess its feasibility and propose an initial approach.