STAGSTER Labs LLP (LLPIN: ACS-0188)D-U-N-S 771775839Hyderabad, India HQBengaluruGlobal delivery24-hour responseSTAGSTER Labs LLP (LLPIN: ACS-0188)D-U-N-S 771775839Hyderabad, India HQBengaluruGlobal delivery24-hour response
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Custom AI workflow diagram showing data ingestion, processing, decision, and output stages with human oversight

AI & Agents

Custom AI Workflows

Pragmatic AI built around your process. Sometimes an LLM, sometimes a Python script.

1

How it works

1

Process Audit

Map your current workflow. Identify bottlenecks. Assess data readiness. Define success metrics.

2

Solution Design

Select the right AI approach (LLM, rule engine, classical ML). Design the data pipeline. Define human-in-the-loop points.

3

Build and Train

Prepare data. Train models or engineer prompts. Develop APIs. Wire up integrations.

4

Validation and Testing

Run accuracy benchmarks on real data. Test edge cases. Cycle through human validation.

5

Deploy and Monitor

Deploy to production. Set up monitoring dashboards. Build feedback loops and retraining schedules.

2

Deep dive

AI is a means, not a goal

We do not start with AI and look for a problem to fit it into. We start with your workflow. We find the parts that are slow, inconsistent, or manual. Then we apply AI only where it creates leverage. Sometimes that means a large language model. Sometimes it means a well-written script. The goal is not to use AI. The goal is to make your process faster and more reliable.

The AutoRehire pattern

AutoRehire scoring engine is a good example. It uses a multi-factor scoring model (not generative AI) to evaluate resumes against job criteria. Faster and more consistent than any human screener. It was built to solve a real bottleneck in the hiring process. Not to demonstrate a technology. That is how we approach every AI workflow.

3

What a custom AI workflow engagement gets you

  • Time savings measured in hours per week against your current process
  • Accuracy benchmarks validated against your real data, not synthetic tests
  • Human oversight where judgment matters, automation where speed matters
  • Monitoring that catches drift or errors before they cause problems
  • Documentation your team can maintain and extend without us
4

Investment

4-10 week engagement, Rs 3L - Rs 15L

Simple automation to complex multi-agent workflows. Ongoing monitoring and model retraining available as retainer.

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