Contact
Start with a conversation.
About a process, data or your team’s daily work. Let’s find where AI can help.
Maciej Rutkowski and Ignacy Bochiński
Partners at WeAreFuture
Talk directly to Maciej or Ignacy.
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.