Public data collection
Business information is gathered from appropriate public sources into a consistent structure.
ProspectLab
Working demo · Independent Noerong product
A lead-data pipeline that collects public business records, removes duplicates, scores fit, and exports clean prospect lists.
IndustryLead intelligence
AudienceLean sales and growth teams
Studio roleData workflow design and engineering
Released2026
The product
Built around the
actual workflow.
ProspectLab turns public business records into a usable prospect list. It prioritizes fit and data quality so teams spend more time starting relevant conversations and less time fixing spreadsheets.
Product approach
Less friction.
More clarity.
Collection, normalization, deduplication, scoring, and export are treated as one traceable pipeline, with quality signals visible before a record reaches outreach.
Core system
What it
brings together.
Deduplication
Repeated companies and contacts are resolved before they inflate a sales list.
Fit scoring
Clear criteria prioritize the records most relevant to the target market.
Clean export
Validated prospects can move into a CRM or outreach workflow without another cleanup pass.
Architecture
Why these
decisions.
PythonData qualityCSV export
The data workflow separates normalization, duplicate removal, fit scoring, and export. Visible quality signals let an operator assess a record before moving it into an outreach system.
Outcome and boundaries
What is built.
What comes next.
Delivered product
A working example of turning inconsistent public business records into a reviewable prospect list.
Before a business launch
This portfolio example is not an automated outreach service. Production collection must use permitted sources and buyer-approved criteria, with applicable privacy and platform requirements reviewed before use.
Independently designed and built by Rongali Chaitanya at Noerong. Scope and acceptance criteria are agreed before a client implementation.
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