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Let AI handle the repetitive judgment calls in your back office

We build server-side AI jobs for work that needs a little judgment but happens at a volume no person wants to do by hand: placing new items into categories, labelling records, extracting specifications from text. The model proposes; the code validates, records where each answer came from and keeps a person in control.

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When this service fits

  • New items arrive every day and someone has to sort, tag or route each one.
  • Supplier data uses its own categories and names, and you need them in yours.
  • Useful facts are buried in free text descriptions and you need them as fields.
  • You tried a chatbot on the problem and could not trust or audit the results.

What you receive

  • A job that runs on a schedule or after an import, on new or changed records only.
  • Structured output checked against a schema; invalid or unanswered items stay pending instead of being guessed.
  • Rules that respect people: a manual decision is never overwritten by the model.
  • Content fingerprints, so an item that did not change is never paid for twice.
  • A spending limit enforced across runs, using the provider’s own token counts.
  • An admin view of what ran, what was accepted and what waits for review.

Scoped separately

  • Agents with open-ended permissions on your servers or accounts. We build bounded jobs with explicit inputs and outputs.
  • Model usage fees, billed by the provider to your account.
  • Labelling large historical archives, estimated separately from the ongoing job.
Example from our own products

New categories placed automatically every night

Cumpără cu AI receives product categories from many shops, each with its own tree. Our 17 departments are the only fixed level. After each nightly import, new categories are placed into a department by Gemini; a sub-category simply joins its parent’s department without a model call. Very broad supplier groups, such as a shop’s “Electronics” umbrella that holds printers, toners and headphones together, are sent to the model case by case instead of inherited.

An administrator can move a category or a single feed category by hand in the configuration panel. A manual placement is marked and never moved automatically again. The initial placement of 5,060 categories was done with Claude, then checked in the same panel.

A second job labels products with a shopper’s words, the audience and specifications the text states, through Gemini’s Batch API at half price. Each answer is validated, archived by content fingerprint and kept apart from the shop’s data; a budget stop ends the run before the agreed amount is exceeded.

Cumpără cu AI · Raftul copiilor · Facebook ads automation · Facebook & Instagram auto-posting

How the work runs

  1. Pick one workflow

    One decision repeated often, with clear inputs, a clear output and a measurable error.

  2. Sample and baseline

    A labelled sample from your real data to measure the model against before anything runs unattended.

  3. Build the job

    Prompt, schema, validation, review states, retries and cost control.

  4. Shadow run

    Results are recorded but not applied, and compared with what people decided.

  5. Go live

    Applied automatically above the agreed quality bar, with a review queue for the rest.

What affects cost and schedule

  • Volume of items per day and the size of any backlog.
  • How subjective the decision is and how errors are corrected.
  • Where the data lives and how the result is written back.
  • Model choice: batch or real time, cost per item, privacy terms.

Questions buyers ask

Is this an “AI agent”?

It is a server-side job that uses a model for a decision and code for everything else. That is what makes it reliable: inputs, permissions and outputs are fixed, and every answer is checked before it changes your data.

What happens when the model is wrong?

Answers that fail validation stay pending. People can correct any decision, and a corrected item is locked against future automatic changes. The shadow run sets the bar before anything is applied.

Can the costs run away?

The job only sends new or changed items, and a hard budget is checked before each batch is sent. Batch APIs cut the price further where an immediate answer is not needed.

Related services

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