AI assistants over approved documents
Systems over documents, catalogs and approved sources, with clear limits and useful records.
Independent technical studio
Fenutech works behind the scenes on B2B projects that need AI prototypes, document assistants, quote automation, operational dashboards, intelligent catalogs and CRM/email integrations.
Systems over documents, catalogs and approved sources, with clear limits and useful records.
Intake, classification, summaries, missing data and review dashboards.
Operational interfaces for requests, status, AI results, exports and manual actions.
A realistic scenario showing the workflow shape and expected result.
The agency owns brand, UX and client relationship. Fenutech builds document organization, review dashboard and email integration behind the scenes.
The client relationship stays with the agency. Fenutech enters where specialist technical delivery is needed and leaves clear notes for the next step.
The system should stay understandable, maintainable and documented after delivery.
AI systems work on defined documents, catalogs and data sources, with clear boundaries for each use case.
Important commercial results can be drafted by AI and approved by a person before being sent.
Questions, results, access and important steps are documented so the system stays easy to understand.
No. If the bottleneck is internal — documents, quotes, email, dashboards — Fenutech can start with a separate tool. If the site or catalog is part of the workflow, it becomes an interface for that process.
For important commercial workflows, the system usually prepares drafts, summaries and suggestions. A person decides what gets sent.
A focused prototype can often be validated in 2-4 weeks when the documents, workflow and internal reviewer are clear.
Yes. Projects are built with standard technologies, clear access and essential documentation so another technical professional can take over if needed.
It depends on the project. Before the system is used in daily work, Fenutech defines which sources are used, what data may pass through external services, what stays internal, what is recorded and which outputs need human approval.
Share the project model, technical role and timeline.