The Challenge
A ClimateTech startup in India was building emissions reporting infrastructure for enterprise clients. Accurate Scope 1–3 reporting required ingesting large volumes of supplier invoices — but those invoices came in every format imaginable.
Data complexity — PDFs, scans, and image-based invoices from different suppliers had wildly inconsistent layouts. Standard extraction tools failed on anything outside a narrow template range.
Scalability ceiling — Manual processing worked at low volume but couldn’t scale with client growth. Each bottleneck created compliance risk: late or inaccurate Scope 3 data undermined the startup’s core value proposition.
Time-to-market pressure — Hiring and onboarding a full internal AI team would have delayed the feature launch by six months or more.
Cost constraints — Full-time AI engineering salaries would have strained a startup operating on limited runway.
The Solution
Superteams deployed a fractional team purpose-built for this use case: two AI engineers specializing in vision and OCR, one LLM engineer for structured outputs, one solution architect, and one MLOps engineer.
The system was built as a FastAPI service with batch ingestion capability. A vision layer handled the hard part — layout analysis, OCR, and VLM prompting working in combination to extract structured data from documents that no single tool could handle alone.
Outputs were validated against a strict JSON Schema using Pydantic, ensuring downstream emissions calculations received clean, well-typed data. PII redaction was built in from day one to meet supplier data handling requirements.
Reporting that previously required weeks of manual invoice collation was reduced to three days.
Results
The startup shipped the feature on schedule. Six months into production, the metrics were unambiguous across all three dimensions they cared about: speed, accuracy, and cost.
The fractional team model proved its value: the startup got specialist AI engineering talent without the hiring timeline, salary overhead, or long-term headcount commitment.