Document processing, internal copilots and data pipelines, with measurable ROI, live in two weeks.
AI automation takes daily, repetitive but cognitive work off your team's plate: document processing, making internal knowledge searchable, writing reports. Not a model, a working pipeline that integrates into your existing systems.
The best place to start is a concrete, measurable use case (e.g. "every incoming contract summarized within 24 hours", or "an internal HR chat that answers based on policies". We don't sell generic AI strategy) we automate one specific process, and scale from there.
Concrete processes with calibrated ROI, not empty promises.
M365, SharePoint, Google Workspace, ERPs, ticketing systems, via APIs and connectors.
Cloud or on-prem option, sensitive data never enters a public model.
At most companies, this is where we start: quick ROI, low risk, immediate trust-building.
OCR, extraction, classification, automated summarization: for contracts, invoices, reports, correspondence.
Search-and-answer assistant on your knowledge base: over policies, SOPs, project documentation.
Data enrichment, automated analysis, scheduled executive reports in natural language, dashboard narratives.
Pick one concrete process, ROI estimate, success criteria.
2–4 week prototype on real data, measurable output, not a demo.
Connect to existing systems (Microsoft, Google, ERP, ticketing, etc.).
Monitoring, fine-tuning, iterative rollout of new use cases.
The approach is industry-specific, different priorities for a bank than a retail business. Here are the verticals where it fits best.