8.0
/ 10
1 evaluations
1.8k Downloads
Overview
Provide structured research on startups, including search, company profiles, funding history, hiring signals, and side‑by‑side comparisons via the startups.in API.
Key Advantages
1.End-to-end startup research workflow: search, detailed profiles, funding rounds, jobs, and comparisons in one tool.
2.Simple, well-scoped HTTP API (search, get startup, jobs, compare) that is easy to orchestrate in multi-step reasoning chains.
3.Good fit for answering natural-language questions like “Is X hiring?” or “Latest funding for Y?” without custom scraping.
4.Supports discovery use cases (by sector/location) as well as deep dives on known companies.
5.Public access without auth reduces friction; optional identity header allows for potential enhanced access.
Use Cases
- Finding startups by sector, geography, or keyword to build prospect or research lists.
- Pulling a structured profile for a given startup (description, sector, location, basic metrics).
- Retrieving funding history, rounds, and investors for due diligence or market mapping tasks.
- Checking whether a specific startup appears to be hiring and what roles they are listing.
- Comparing two startups side by side on key dimensions (sector, size signals, funding).
Evaluation Scores
8.0
/ 10
Reliability
7.0
Functionality
8.2
Usability
8.0
Safety
8.8
Performance
7.5
Compatibility
8.5
Based on 1 evaluation · Latest: 3/19/2026
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Evaluation History (1)
8.0/103/19/2026▼
OS: win32-x64LLM: z-ai/glm-5-turbo
**Quick judgment**
A strong, focused tool for startup intelligence and competitive research, especially when you need structured funding, hiring, and comparison data without building your own scrapers. Best used as a domain-specific complement to general web search.
**Key strengths**
- Covers the full basic workflow: discovery → details → funding → jobs → comparison.
- Clean, minimal API surface (search, startup detail, jobs, compare) that aligns well with typical user queries.
- Public, no-auth baseline access simplifies integration and reduces friction.
**Main risks / limitations**
- **Coverage & freshness unknown**: startups.in’s database scope, update frequency, and global coverage are not documented; some companies or recent rounds may be missing or stale.
- **Data completeness**: early-stage or small-region startups may have sparse profiles, leading the LLM to overgeneralize or fill gaps if not handled carefully.
- **External dependency**: tool quality depends on startups.in uptime, latency, and rate limits; outages will degrade the skill.
- **No ground-truth guarantees**: funding and valuation numbers are likely aggregated from public sources and may lag official filings.
**Recommended scenarios**
- Market mapping and lead research (e.g., “AI startups in Berlin with recent funding”).
- Quick due diligence summaries (“Tell me about Stripe and its latest funding”).
- Hiring and talent-signal checks (“Is Vercel hiring, and for what roles?”).
- Comparisons for strategy decks or analysis (“Compare Notion and Coda on funding, team size signals, and hiring”).
Use with caution for decisions requiring legally or financially precise data; cross-check critical funding or valuation figures with primary sources where possible.
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