Separate launch-day crash bugs from noisy 1-star pricing rants.
Drop your CSV here
or click to browse your files · CSV only
When to use App Review Crash & Bug Miner
Triage v2 launch feedback and isolate critical P0 bugs within 1 hour
Extract hardware-specific issues (e.g. Samsung Galaxy S24, iPhone 16 Pro)
Filter out emotional 1-star reviews about price or icon changes
Why standard spreadsheets and manual sorting fail on App Review Crash & Bug Miner
The Latency & Fatigue Bottleneck
When operations or revenue teams download raw data dumps with 2,000 to 25,000 rows, team members spend an average of 4.5 hours manually skimming rows, applying ad-hoc Excel autofilters, and deleting records. Human decision fatigue sets in after only 200 rows, leading to false positives and accidental deletion of valuable accounts.
Downstream API & Credit Waste
Uploading unfiltered CSVs directly into downstream enrichment platforms (such as Clay, ZoomInfo, or email verification tools) burns credits on contacts you will never reach. At an average of $0.15–$0.40 per enrichment lookup, running a dirty list wastes hundreds of dollars in under five minutes.
RFC 4180 Ingestion
Streams raw CSV bytes into an in-browser Web Worker, automatically removing UTF-8 BOM signatures and preserving multiline quotes.
Natural Language Compile
Gemini Flash compiles your plain-English prompt into structured rule trees, exclusion lists, and weighted signal dictionaries.
Zero-Cost Evaluation
Needle System 1 classifies 1,000 rows in ~8ms with 0 token consumption. Your raw data never leaves your browser sandbox.
CWE-1236 Clean Export
Sanitizes dangerous spreadsheet formula prefixes (=, +, -, @) and delivers ready-to-import CSVs.
Pay only for what you export. Free 100 rows preview always included.
Up to 1,000 rows exported. Ideal for targeted prospect lists and weekly bug triages.
Up to 5,000 rows exported. Perfect for monthly support ticket dumps and catalog cleanups.
Up to 25,000 rows exported. For comprehensive vendor audits, log analysis, and CRM migrations.
Frequently Asked Questions
How does it distinguish a bug from a bad review?
Needle scans for diagnostic tokens like 'force close', 'black screen', 'freeze', 'after update', and hardware models while down-ranking generic sentiment.
