Article summary
Assess API need through volume, latency, exception handling, audit and engineering readiness; AIPUSH’s current TXT-to-Excel workflow must not be presented as an API.
A company needs a number-checking API only when the process genuinely requires frequent or low-latency machine-to-machine calls—not because the dataset looks large. Without defined input rules, exception states, idempotency, authorization and rollback, an API only propagates errors faster. AIPUSH currently operates through TXT upload and Excel export and must not be marketed as an interface it does not provide.
Measure the actual burden of the file workflow
Record weekly batches, rows per batch, preparation labor, acceptable wait, Excel acceptance time, rework and business deadlines. An occasional hundred-thousand-row overnight job may need an API less than hundreds of small events whose decisions cannot wait.
| Dimension | File workflow fits | Integration may fit |
|---|---|---|
| Frequency | Scheduled daily/weekly batches | Continuous event stream |
| Latency | Hours or overnight acceptable | Action needs minute-level response |
| Exceptions | Human review is practical | Mature automated queues exist |
| Engineering | Analyst-led operation | Services, monitoring and on-call ownership |
An API requirements document answers eight questions
Who calls it? What fields enter? Where are country rules? How is authentication handled? What limits apply? How is idempotency guaranteed? How are unknown and errors represented? Who owns retries and deletion? “Later” for any answer signals incomplete readiness.
A file workflow can still be standardized
| Step | Automation asset | Human gate |
|---|---|---|
| Export | Stable TXT generator | Provenance and permission approval |
| Upload | Batch naming and hash | Task-choice confirmation |
| Return | Excel schema check | Blank/collision review |
| Load | Staging and append-only observations | Exception closure |
Describe the current AIPUSH workflow accurately
A user uploads a one-phone-per-line TXT, chooses a platform task and downloads Excel containing the service’s fields. An automation aspiration is not an existing API, and product copy must not claim direct CRM integration.
Run a shadow integration first
Even if an interface is evaluated later, write automated results into a shadow table that cannot send, delete or overwrite master data. Run it beside the manual batch for a period and compare counts, states, latency and collisions.
Idempotency matters more than speed
Repeated calls for the same phone, task and version need a request_id so retries do not create conflicting business actions. A timeout is not proof of failure; callers need status lookup or a safe retry contract.
Unify the error model before transport
Separate invalid_input, unknown, not_available, processing_error, rate_limited and explicit negative. An API that turns every exception into false is more dangerous than a manual workbook because its error enters downstream instantly.
Authorization and deletion cannot be bolted on later
A calling service receives the minimum fields, credentials rotate and logs avoid unnecessary full phones. Support batch deletion, purpose-based expiry and an audit of who called what.
Evaluate total economics
Count preparation/import labor saved and waiting loss avoided, then include development, monitoring, incidents, audit and security. Multiplying one removed upload by an hourly wage understates long-term operation.
The decision threshold
Start an API project only when the file workflow is stable, the business truly needs lower latency, exceptions can be isolated automatically, engineering owns runtime operations and the provider formally offers the matching capability. Until then, a reproducible TXT/Excel process often delivers the higher return.
