Bytesicht audits what you have, connects to the systems you want to keep, and builds a focused workflow with clear controls and acceptance criteria.
Timelines assume a bounded scope and timely access. Dependencies are made explicit before the work begins.
Map the current process, documents, handoffs, systems, permissions, exceptions, baseline effort, and where AI can or cannot help.
Expose a bounded set of tools or data from an existing system through MCP, an API adapter, or another narrow integration interface.
Build one useful workflow end to end using representative inputs, real rules, a review path, an integration target, and measurable acceptance criteria.
The audit is deliberately concrete. It follows the documents and decisions through the systems where work actually happens.
Triggers, handoffs, decisions, exceptions, bottlenecks, and ownership.
Formats, variation, volume, fields, quality, relationships, and retention.
Sources, destinations, APIs, databases, exports, identity, and current automation.
Permissions, privacy, approval boundaries, auditability, and failure handling.
Existing AI services, OCR, cloud capabilities, agent tooling, and where they fit.
Baseline metrics, evaluation examples, success criteria, and the rollout decision.
An MCP server can expose selected data and actions from an existing system. The useful work is defining the boundary: authentication, permissions, tool inputs, error behavior, approvals, and logs.
A bounded one-week path
Bytesicht is intentionally small. You work directly with Milan Danilovic from process mapping through implementation, evaluation, and handover.
That keeps technical decisions close to the operational reality and avoids a sales-to-delivery handoff before the workflow is properly understood.
About BytesichtTell us what is handled manually today, which systems are involved, and what a useful result would change. We will recommend the smallest sensible next step.