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AI Automation

Most ‘AI automation’ is a Zapier screenshot. AppsAura automates the ugly middle of operations software: classify a complaint, extract fields from a document, suggest the next status. Vistarx-style workflows already need those steps. The model proposes; the system of record still requires a role.

India-based global teamStartups, SMBs and enterprises worldwide
Architecture-firstBuilt to scale cleanly
Transparent deliveryMilestones you can track
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Service overview

We start from the existing process, not from a model. If a deterministic parser works, we use it. AI sits on the residual: messy text, photos of labels, inconsistent supplier emails. Every automated write has an idempotency story and a way to undo.

Problems we solve

  • Automating a broken process, faster.
  • Silent writes to production with no audit.
  • OCR or extraction that is 90% right and 10% catastrophic.
  • No owner when the automation fails on a weekend.

What we build

  • Classification and extraction into existing fields
  • Human-in-the-loop queues for low confidence
  • Retries, dead letters and alerts
  • Role-based undo
  • Batch and near-real-time modes
  • Cost and latency budgets per job type

Benefits

  • Hours back on repetitive classification — without deleting the operator.
  • Automation that matches how AppsAura already ships ops software.

Use cases

  • Route complaints into the right queue.
  • Draft structured fields from a messy email.
  • Flag missing readings or documents for a human.

Technologies

PythonNode.jsPostgreSQLAWS

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