AI integrations
We integrate artificial intelligence into the processes that consume the most time, with results that can be measured.
ABOUT THE SERVICE
Artificial intelligence integrated into real work.
AI integrations become useful when they are connected to concrete data, documents and processes. We identify the cases with measurable value and choose the model, the tooling and the level of control that suit each business.
We develop assistants for clients and teams, intelligent search, document processing, request classification, quote generation and automated reporting. Solutions can use OpenAI, Anthropic or Google models, or your own infrastructure.
We start with a controlled prototype, evaluate the quality of the output, and only integrate the solution into your CRM, website, application or internal system once it has been validated.
WHAT WE CAN DEVELOP
Available services
We can combine them into a complete project, or you can commission them separately.
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01
AI strategy and roadmap
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AI assistants for clients
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AI assistants for teams
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04
AI connected to documents
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AI connected to CRM
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Intelligent search
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Document processing
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Request classification
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Lead qualification
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Quote generation
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Content generation
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Data analysis
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AI-generated reports
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Process automation
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15
AI model integration via API
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AI integration into existing products
FAQ
Frequently asked questions
Which processes are worth automating with AI?
Repetitive tasks involving many texts or documents and verifiable outputs are a useful starting point. We assess volume, data quality and the cost of errors; sometimes rule-based automation is a better fit than AI.
Can an AI assistant work with our documents and CRM?
Integration is possible if the systems provide the required access. We define which sources it can consult and which actions it can take, then test real scenarios; connecting data does not mean granting unrestricted access.
How do we limit incorrect answers and unwanted actions?
We use defined sources, representative test cases and clear action limits. For consequential operations, we design human verification or approval; no model should be treated as infallible.
What happens to data sent to the AI provider?
The flow depends on the provider, chosen service and configuration. Before integration, we clarify what data is sent, where it is processed and which retention terms apply, then limit information to what the task requires.
How do we measure whether an AI integration delivers value?
We compare a baseline process with a pilot: time spent, output quality, required corrections and cost per task. Expansion decisions are based on these measurements rather than the impression of a demonstration.