AI data enrichment engine case studyHours of manual company research became scored, searchable data on demand.
A client needed to evaluate large numbers of companies far faster than any team could by hand.
Illustrative interface with example figures.
A client needed to evaluate large numbers of startups quickly. I built a pipeline that collects and cleans company data with rules, uses AI only for classification and scoring, and lands it as structured data — now a live tool in commercial use.
Too many companies to research by hand.
A client needed to evaluate large numbers of companies/startups — pulling scattered public information together and judging each one — far faster than any team could by hand.
Messy data, real judgment — and an AI budget.
The source data is messy free-text from many places, and the judgment genuinely needs interpretation — but most of the work (collection, cleaning, validation) doesn't, and shouldn't burn AI budget.
Clean, scored, queryable company data.
A pipeline that collects and enriches company data, uses AI to classify and score each record from messy descriptions, and lands it as clean, structured, queryable data the client's team can act on.
Deterministic where possible, AI where it counts
- 01Collect & enrichPublic info from many places
- 02Dedup & validateStrict rule-based first pass
- 03AIClassify & scoreStructured, validated output
- 04Queryable dataPostgreSQL + export
Deterministic where possible, AI where needed.
Rules-based first pass
Strict collection, deduplication and validation — fast and cheap.
AI for judgment only
Classification and scoring with validation and structured output downstream code can trust.
Isolated AI adapters
A model or prompt change never breaks the deterministic pipeline.
The calls that shaped the build
A model or prompt change should never break the deterministic pipeline. The adapter isolates AI calls so they can change independently.
Downstream code needs to trust every record. Structured output plus validation means a bad response is caught, not stored.
A live tool in commercial use.
Sikandar has delivered outstanding quality of work. He drove the project with autonomy and has a solution-focused mindset toward creating unique, cost-saving, and data-smart solutions. He took on a large scope with a wide breadth of expertise. I would highly recommend working with Sikandar, who handles his work with expertise and professionalism.
