WeAreFutureAI Check
AI Check
Find your starting point with AI.
20 questions. A clear picture of your situation and three actions to plan with your team.
Findings are based on your answers. AI Check is not a compliance or security audit.
Start hereAI for teamsFrom shared rules to everyday AI use and process change. Choose the right level for your team.AI for teams →Pharma10% → 87%From a niche curiosity to everyday work: adoption of the internal AI assistant grew from 10% to 87%.See more →
- Level 1 · Whole companyAI foundationsThe Hi_AI e-learning platform: the team learns what AI can do, shared rules and safe working practices. People try first tasks they can put into practice straight away.
- Level 2 · Power usersAI practitionersPeople use AI on their own everyday tasks. With a trainer, they improve how they work and assess time saved and the quality of results.
- Level 3 · Transformation leadersAI First: processes redesignedLeaders select processes worth changing with AI. Teams test new ways of working on demonstrators, assign responsibilities and measure the value of the change.
- Tool · AnthropicClaude for businessSelection, setup and adoption.
- Tool · Microsoft 365Microsoft Copilot for businessAI in the Microsoft 365 environment.
- Diagnosis · Usage and risksAI tools auditWe check who uses AI and how.
Start hereAI for organizationsAgents for specific tasks, on one engine for your whole company.AI for organizations →ExploreQuoting agentAgents perform specific tasks. We connect them to your systems and develop them with your AI Engine.See the case →
- Quoting agentReads enquiries, selects products and prepares quotes. The team checks the result before sending it to the customer.
- Knowledge agentAnswers questions using company knowledge. Points to current sources in the tools the team already uses.
- Document agentReads documents and checks completeness. Passes data onwards and routes exceptions to a person.
- Product agentSelects and configures products using company rules. Connects parameters, availability and documentation.
- Tender agentBrings together requirements, deadlines and attachments. Helps prepare a response for the team to review.
- Custom agentWhen no module fits, we build an agent for your process. On the same AI Engine.
- Working with us
- How we work togetherImplementation team, responsibilities and AI Engine development.
- Start with AI in 90 daysOur AI consultant inside your company for a quarter: roadmap, rules and adoption framework.
Start hereData and contextShared knowledge of products, customers and work. A foundation for people and agents.Data and context →ExploreKnowledge grows through workShared knowledge of products, customers and work. A foundation for people and agents.See the case →
- AI EngineYour company’s AI architecture: what it is made of, how it works and how we build it.
- Data foundationsContext Lakehouse connects data, documents and company context. It covers source integration, quality, security and shared business definitions.
- System integrationsWe connect ERP, CRM, Microsoft 365 and Helpdesk to AI Engine. MCP gives agents controlled access to agreed tools.
- Your AI environmentAzure is the starting point. The most sensitive data can be processed by local models on company servers. We select other clouds and fully on-premise environments together with IT.
Business benefitsCase studiesWe start from a problem your board knows and from the result, not from technology.All case studies →Quoting agent7 days → 1 dayResponse time for enquiries handled by the agent. It reads the enquiry with attachments and prepares a quote, which a salesperson approves.See the case study →
- A quote ready in one dayQuoting agent
- Product selection in a few minutesProduct agent
- Documents without manual retypingDocument agent
- Fast access to company knowledgeKnowledge agent
- People who work with AI every dayAI adoption programme
- Employees build their own toolsAI adoption programme
- Directors show prototypes, not slidesProgramme for directors
- AI that keeps data inside the companyAzure is the starting point. The most sensitive data can be processed by local models on company servers. We select other clouds and fully on-premise environments together with IT.