We build our own products
CORBELIA demonstrates our ability to turn knowledge, data, software and AI into a complete corporate platform.
Discover CORBELIAWe build the AI that works in your business.
We design, develop and implement Artificial Intelligence solutions connected to your data, processes, applications and teams.
From a model to a solution
AI starts with the model. Value emerges when it is integrated into your business.
A model provides capability. Turning it into a business solution means connecting it to the organisation's knowledge, software, permissions, validations and decisions.
DataKnowledgeProcesses
SoftwareHuman controlApplied AI
What we build
Our own products. Bespoke solutions. AI in production.
We do not start with a particular tool. We start with the problem, its context and the outcome it needs to produce.
We develop the solution that fits
Applications, agents, automations and AI systems designed for a specific process, need or product.
Explore bespoke developmentWe take AI into production
Definition, architecture, integration, validation, implementation and evolution within real business environments.
See how we implementA platform developed by deepdatIA
CORBELIA
Documents · Knowledge · Decisions
Our main product is tangible proof of what it means to build enterprise AI: architecture, corporate knowledge, document analysis, data, agents, permissions, integrations and control.
Corporate knowledgeDocument AIData and BIAgentsAutomationIntegrationsPermissionsTraceability
A system of capabilities
Enterprise AI does not work in isolation.
Each solution combines the capabilities the problem requires and connects them through an architecture designed to evolve.
AI agentsSpecialised capabilities for specific tasks and processes.
Knowledge / RAGCorporate knowledge accessible with context and permissions.
Document AIDocument reading, extraction, classification, validation and generation.
Data and BIQuestions, analysis and decisions supported by reliable information.
AutomationProcesses coordinated across people, AI and applications.
IntegrationsConnection to the tools and systems the organisation already uses.
AI applicationsInterfaces and software designed to work in a real context.
Governance and observabilityPermissions, validation, traceability, measurement and evolution.
From problem to production
A useful idea only creates value when it truly works.
Understand the problem
Prioritise the opportunity
Design the architecture
Build and test
Integrate systems
Implement and measure
Evolve
Human + Artificial Intelligence
Our team does not end where people end.
Professionals and Artificial Intelligence systems work together throughout analysis, engineering, testing, documentation and evolution. Capacity increases; judgement and responsibility remain human.
People
- Business judgement
- Architecture and design
- Decisions and validation
- Responsibility
AI
- Analysis and research
- Programming and testing
- Documentation
- Support for evolution
Problems we can solve
Specific cases before abstract technology.
Make internal information searchable
Connect documentation and knowledge to answer with context, permissions and sources.
Process large volumes of documents
Classify, extract, verify and transform information within a controlled flow.
Automate processes across applications
Coordinate tasks, communications, deadlines and validations across systems and teams.
Create a new AI application
Turn a specific need into software, agents or a vertical solution.
Engineering principles
Powerful technology. Understandable architecture. Real control.
Usefulness before novelty
AI has value when it improves a process, a decision or a specific capability.
The problem before the tool
First we define what needs to improve. Then we select the technology.
Control based on context and risk
Autonomy is designed; human validation is introduced wherever it adds safety.
Integration rather than isolation
AI must work with existing data, documents, applications, processes and teams.
Start specific and evolve
We solve one initial problem well and build a foundation that can grow.
Technology independence
The architecture takes precedence over any particular provider, model or tool.
Is there a process you think AI should be able to improve?
Tell us what happens today, what should change and what outcome you need. We will start by understanding the problem.