All services · AI for one work task

One workflow · verifiable output

From one document or request type to a register

For a coordinator, administrator, or manager whose team transcribes recurring requests into a spreadsheet. We choose one type and one processing route: for example, service requests from an agreed folder into a draft register for review.

Denis Skripnik — a blind specialist in working with AI agents. I examine the task, configure the workflow, and work with you to verify the result against agreed rules.

AI agent setup is already selected in the brief. Name the scenario: “From one document or request type to a register”. Describe the files or systems you use, the result you need, and any exceptions. Start with a description of an anonymized sample.

Input: one type and an agreed source

• Samples of one document or request type, including incomplete and difficult examples. We assess formats and scan quality before starting.
• Register fields, required values, date and status rules, and examples of a correctly completed row.
• An authorized folder or export and personal-data handling rules. Initial access to an entire mailbox or CRM is not needed.

Output: a draft register with source references

• A draft table or register with extracted fields and a reference to the source document, page, or passage where the agreed format allows.
• Missing fields marked as missing; unreadable or contradictory values flagged for review. Guesses are not recorded as facts.
• An exception list and possible duplicates for an employee to review. Originals are read-only and unchanged; drafts are stored separately.

Example: an incomplete request stays incomplete until checked

This is an illustrative example, not a client case study. A service request names the equipment and problem, but omits its serial number and has an unreadable date on the scan. The draft contains confirmed fields and a source reference. The serial number is marked missing and the date requires review.

An employee opens the source, obtains missing details, and confirms the row. The workflow does not invent a number, correct the original, send a reply, or independently create a production-system record.

What we configure for this workflow

• Read-only access to the agreed source, a field schema, and data extraction without modifying originals.
• Format and required-field checks; OCR or AI only where needed and permitted for the data.
• A separate draft, source references, exception queue, export, and test set with gaps, unreadable text, and possible duplicates.

Limits and quality checks

This is not legal or accounting advice, document authentication, or a replacement for the responsible employee. Another document type, intake channel, or production-system write requires separate agreement. Possible duplicates are not merged automatically.

Before implementation, we agree fields to verify, acceptable errors, and mandatory stop conditions. Acceptance compares drafts against sources and checks that omissions and contradictions remain visible. Personal data is not sent to an external model without an agreed basis and processing conditions.

Sources, access, and your responsibilities

• An anonymized export is enough to start: remove information that could identify a person, business secrets, and unnecessary fields. Do not put passwords or keys in the brief.
• For implementation, we agree the minimum necessary permissions, preferably a dedicated account with read access only to selected sources. An export instead of production-system access is an acceptable alternative.
• You provide lawfully available samples, rules, an authorized environment, and a designated reviewer who resolves disputed data. We agree storage, deletion, and permitted model-provider data transfers in advance.

Acceptance, instructions, and training

At acceptance, we run the chosen workflow in the customer’s environment. We agree criteria, a test set with ordinary and disputed examples, output format, and error reporting before implementation. Handover provides operating and review instructions and training for the responsible employee; their format and scope are specified in the proposal.

Iteration count, correction of nonconforming results, requirement changes, and support after acceptance are agreed separately before starting. Unlimited revisions and ongoing support are not implied.

Timing, price, and external expenses

The price and exact duration are confirmed after reviewing a sample and before work starts. They depend on data quality, formats, volume, environment, and review requirements. Existing service price guidance is not a fixed quote for this scenario.

If a sample is insufficient to define the scope reliably, a paid discovery or bounded pilot can be agreed separately, with its own deliverable and criteria. It does not automatically commit either party to full implementation.

Server costs, paid services, and model usage are separate from implementation fees. Before starting, we agree what is necessary, who pays for accounts, and spending and processing limits. Payment for the work follows scope and quote confirmation only.