We extract startup profiles, funding rounds, investor portfolios, and valuation histories from CB Insights. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Company Profiles objects from cb-insights.com. All fields typed and schema-versioned.
"company_id": "CBI-98421", "company_name": "Stripe", "founded_year": 2010, "total_funding": 8700000000.0, "last_valuation": 50000000000.0, "operating_status": "Active", "hq_location": "San Francisco, CA", "primary_industry": "Fintech"
| # | company_id | company_name | website_url | description | founded_year | total_funding |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Funding Rounds objects from cb-insights.com. All fields typed and schema-versioned.
"round_id": "FR-104928", "company_name": "Stripe", "round_type": "Series I", "announced_date": "2023-03-15", "money_raised": 6500000000.0, "currency": "USD", "post_money_valuation": 50000000000.0, "lead_investor": "Andreessen Horowitz"
| # | round_id | company_name | round_type | announced_date | money_raised | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Investor Profiles objects from cb-insights.com. All fields typed and schema-versioned.
"investor_id": "INV-4421", "investor_name": "Sequoia Capital", "investor_type": "Venture Capital", "aum": 85000000000.0, "total_investments": 1420, "successful_exits": 312, "preferred_stages": "['Seed', 'Series A', 'Series B']"
| # | investor_id | investor_name | investor_type | aum | hq_location | total_investments |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for M&A Activity objects from cb-insights.com. All fields typed and schema-versioned.
"deal_id": "MA-88321", "acquirer_name": "Adobe", "target_name": "Figma", "acquisition_date": "2022-09-15", "deal_amount": 20000000000.0, "currency": "USD", "deal_type": "Acquisition", "target_industry": "Design Software"
| # | deal_id | acquirer_name | target_name | acquisition_date | deal_amount | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Competitor Graphs objects from cb-insights.com. All fields typed and schema-versioned.
"source_company": "Plaid", "target_competitor": "MX", "similarity_score": 0.92, "shared_investors": 2, "market_overlap": "Financial Data APIs", "funding_disparity": 210000000.0
| # | source_company | target_competitor | similarity_score | shared_investors | market_overlap | category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our CB Insights scraper handles every layer of the platform: startup profiles, funding rounds, cap tables, and investor portfolios. We manage the JavaScript rendering, session management, and anti-bot circumvention.
Extract founding year, total funding, valuation, employee count, and industry classification for any private company.
Capture round type, capital raised, pre-money valuation, lead investors, and participating syndicates.
Map venture capital firms to their active investments, successful exits, and preferred funding stages.
Track step-ups and down-rounds over time with timestamped valuation metrics per funding event.
Extract acquisition targets, acquirers, deal amounts, and strategic rationale from the M&A database.
Map competitive landscapes using CB Insights similarity scores and shared investor overlap.
Monitor patent filings and technology trend mentions associated with specific startups.
Extract founder backgrounds, board members, and key executive transitions.
Run continuous pipelines at daily or weekly cadences with change-detection diffing to track new deals.
Brief in. Clean data out.
Provide company URLs, investor names, or industry keywords. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, session management, and Datadome bypass for cb-insights.com.
Schema validation, null-rate checks, and sample data review before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
CB Insights protects its proprietary data with strict access controls and aggressive bot mitigation. Here is how we stay resilient.
CB Insights uses sophisticated bot protection to block automated extraction. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to bypass Datadome.
Company profiles and competitor graphs are heavily JavaScript rendered. We run full Playwright browser sessions with JavaScript execution and lazy-load triggering to capture data that headless HTTP clients miss entirely.
The DOM structure changes frequently. Our selector strategy uses multiple fallback chains per field, including CSS selectors, XPath, and text-pattern matching, ensuring layout changes do not break your data pipeline.
For large company catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, schema drift, and coverage drops. SLA uptime is contractual.
Venture capital firms track early stage funding rounds and founder movements to identify breakout startups before competitors.
Corporate strategy teams monitor competitor funding, valuation step-ups, and M&A activity to benchmark market position.
Corporate development teams filter private companies by employee count, funding stage, and industry to build acquisition pipelines.
Analysts aggregate total capital deployed across specific tech verticals to quantify market momentum and investor sentiment.
B2B sales teams use recent funding events as trigger signals to pitch high growth startups with fresh capital.
Private equity firms map shared investor networks and historical valuation trends to validate target company narratives.
"CB Insights maps the entire private market ecosystem. Extracting that graph into a relational database requires bypassing enterprise grade bot protection."
Extracting intelligence from CB Insights requires more than standard HTTP requests. Their infrastructure relies on aggressive rate limiting, complex JavaScript rendering, and Datadome bot protection. DataFlirt absorbs that complexity, handling session management and proxy rotation so your analysts can focus on market signals.
Everything supported by our cb-insights.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across US regions. Rotation happens per request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About cb-insights.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated company, funding, and investor data. We do not extract personal data, circumvent authentication walls, or steal proprietary analyst reports. Clients should review CB Insights ToS and consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for rate limits in real time and trigger pool rotation automatically.
No. DataFlirt focuses strictly on public web data. We do not bypass authentication walls to extract premium research reports or proprietary cap table data restricted to paid users.
Pipelines can be configured to run daily or weekly. Our change detection system identifies new funding rounds and valuation updates, delivering diffs to your warehouse within hours of the crawl completing.
Yes. We extract the full list of active investments, historical exits, and co-investor networks for any specified venture capital firm or angel investor.
Our smallest packages start at a defined list of 5,000 companies or investors with weekly delivery. For larger market mapping requirements, we price based on volume and delivery frequency. Contact us for a scoped quote.
Absolutely. We provide a sample run of up to 100 company profiles as part of the pre-engagement scoping process so you can validate schema fit and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off startup catalogue dump or a continuous funding monitor across 100K companies, we scope, build, and operate the pipeline. Tell us what you need.
