Product Hunt Launch

Overview

Product Hunt Launches capture companies that are actively going to market with new products. Each launch includes engagement counts, AI analysis of the product, and ready-to-use outreach hooks.

We pull Product Hunt launches daily and enrich each one with analysis. Our model writes a summary, extracts pain points and use cases from the product description, and generates outreach hooks. Signals are tagged (startup, B2B, AI product, high performer, featured) for easy filtering.

Signal Subtype

Signal	Subtype Enum	Description
Product Hunt Launch	`companyProductHuntLaunch`	All Product Hunt launches with bundled metadata

Each signal contains tags for filtering by characteristics:

Tag	Description
`startup`	Early-stage company
`b2b`	B2B product
`ai-product`	AI/ML related product
`high-performer`	Launch with high vote counts
`featured`	Featured by Product Hunt

Schema

{
  "signal_id": "ph-1261594",
  "signal_type": "producthunt-launch",
  "signal_subtype": "companyProductHuntLaunch",
  "association": "company",
  "detected_at": "2026-09-27T07:01:00Z",
  "company": {
    "name": "HFT Trading Bot Development",
    "domain": "firebeetechnoservices.com",
    "linkedin_url": "linkedin.com/company/firebeetechnoservicespvtltd",
    "industries": [
      "Technology, Information And Internet"
    ],
    "employee_count_low": 11,
    "employee_count_high": 25
  },
  "data": {
    "product_name": "HFT Trading Bot Development",
    "product_tagline": "HFT Bots Built Around Deterministic Order Execution",
    "product_description": "Build an HFT trading bot around deterministic execution rather than basic automation. We engineer the system to reduce latency across market-data handling,...",
    "product_hunt_url": "https://www.producthunt.com/products/crypto-copy-trading-software-development",
    "product_hunt_id": "1261594",
    "website_url": "https://www.firebeetechnoservices.com/blog/hft-trading-bot",
    "thumbnail_url": "https://ph-files.imgix.net/8f15e8ce-63f7-4ea6-80f3-0edf505c5cf5.png?auto=format",
    "slug": "hft-trading-bot-development-3",
    "votes_count": 1,
    "comments_count": 0,
    "created_at": "2026-09-27T07:01:00Z",
    "makers": [
      {
        "name": "Aana Ethan",
        "username": "aana_ethan1"
      }
    ],
    "source_url": "https://www.producthunt.com/products/crypto-copy-trading-software-development",
    "summary": "HFT Trading Bot Development — a service to build deterministic, low-latency execution architectures for high-frequency trading, important to trading firms seeking predictable order timing and microsecond performance.",
    "detail": "Positioned as a specialist engineering offering for prop trading firms and hedge funds, it differentiates by focusing on deterministic execution behavior and...",
    "relevance": 0.7,
    "confidence": "medium",
    "sentiment": "neutral",
    "is_ai_product": false,
    "is_b2b": true,
    "primary_topic": "Finance",
    "topics": [
      "HFT",
      "Algorithmic Trading",
      "Trading Infrastructure",
      "Low Latency",
      "Fintech"
    ],
    "pain_points_extracted": [
      "high execution latency across market-data handling, strategy processing, and order routing",
      "unpredictable timing/latency spikes under high-throughput conditions",
      "complex or unmanageable codebases in trading systems",
      "order routing bottlenecks and non-deterministic execution behavior"
    ],
    "use_cases_extracted": [
      "building HFT trading bots with deterministic order execution",
      "reducing end-to-end latency across market-data, strategy, and order routing pipelines",
      "deploying high-throughput trading systems with predictable timing characteristics",
      "refactoring/trading system architecture to improve maintainability and performance"
    ],
    "outreach_hooks": [
      "Are you seeing latency jitter or timing unpredictability during peak market conditions that hurts execution quality?",
      "We specialize in deterministic execution layers that make order timing reproducible — would your quant/dev team be open to a latency and determinism audit?",
      "Can we review your market-data and order-routing stack to identify microsecond-level improvements that reduce slippage?"
    ],
    "tags": [
      "b2b",
      "startup"
    ],
    "revenue_range_low": 1000000,
    "revenue_range_high": 5000000
  }
}

Field Reference

Core Fields

Field	Type	Description
`signal_id`	string	Unique identifier for this signal, for example `ph-1261594`
`signal_type`	string	Always `"producthunt-launch"`
`signal_subtype`	string	Always `"companyProductHuntLaunch"`
`detected_at`	string (ISO 8601)	When this signal was detected
`association`	string	Always `"company"`

Company Object

Field	Type	Description
`company.name`	string	Company or product name
`company.domain`	string	Primary website domain
`company.linkedin_url`	string	Company LinkedIn URL (if available)
`company.industries`	array	Company industries (if available)
`company.employee_count_low`	integer	Lower bound of the employee range
`company.employee_count_high`	integer	Upper bound of the employee range

Product Information

Field	Type	Description
`data.product_name`	string	Name of the launched product
`data.product_tagline`	string	Product tagline
`data.product_description`	string	Full product description
`data.product_hunt_url`	string	Product Hunt page URL
`data.product_hunt_id`	string	Product Hunt unique ID
`data.slug`	string	Product Hunt post slug
`data.website_url`	string	Product website URL
`data.source_url`	string	Source URL for the signal
`data.thumbnail_url`	string	Product thumbnail image

Engagement Metrics

Field	Type	Description
`data.votes_count`	integer	Total upvotes
`data.comments_count`	integer	Total comments
`data.created_at`	string (ISO 8601)	Launch timestamp

Makers and Categorization

Field	Type	Description
`data.makers`	array	Makers of the product, each with `name` and `username`
`data.topics`	array[string]	Product Hunt category tags
`data.primary_topic`	string	Primary category
`data.is_ai_product`	boolean	AI/ML related product
`data.is_b2b`	boolean	B2B product (vs B2C)

Sales Intelligence

Field	Type	Description
`data.pain_points_extracted`	array[string]	Problems the product solves
`data.use_cases_extracted`	array[string]	Target use cases and personas
`data.outreach_hooks`	array[string]	Ready-to-use conversation starters
`data.revenue_range_low`	integer	Lower bound of estimated company revenue (USD). Present only for a small share of launches.
`data.revenue_range_high`	integer	Upper bound of estimated company revenue (USD). Present only for a small share of launches.

Metadata

Field	Type	Description
`data.summary`	string	1-sentence launch summary
`data.detail`	string	2-3 sentence analysis
`data.sentiment`	string	Overall tone of the launch: `positive`, `neutral` or `negative`
`data.relevance`	float (0-1)	Score indicating how actionable this signal is for sales outreach (0.0-1.0, where 1.0 is highest). Higher values reflect greater commercial relevance based on factors like event magnitude, recency, and potential impact on buying decisions
`data.confidence`	string	How certain the system is that the signal classification is accurate. `high` = strong textual evidence supports the categorization, `medium` = probable but some ambiguity exists, `low` = inferred with limited direct evidence
`data.tags`	array[string]	Signal tags for filtering (see the tags table above)

API Usage

Generate Insights API

{
  "insightSubtype": "companyProductHuntLaunch",
  "contactEmail": "[email protected]"
}

Generate Content API

{
  "enabledInsights": ["companyProductHuntLaunch"]
}

To exclude:

{
  "disabledInsights": ["companyProductHuntLaunch"]
}

Filtering by Tags

Use the data.tags field to filter signals by characteristics:

-- High-performing AI products
SELECT * FROM signals 
WHERE signal_subtype = 'companyProductHuntLaunch'
  AND data.tags LIKE '%high-performer%'
  AND data.tags LIKE '%ai-product%'

Example Outputs

High Performer:

"Congrats on the launch - 450 votes in the first day is no small feat. Curious what growth channels you're doubling down on post-launch?"

AI Product:

"Saw Acme AI's launch this week - the positioning as an AI-native Zapier alternative resonates with what we're hearing from the market. Would love to compare notes on how you're thinking about enterprise adoption."

Coverage

Refresh: Daily
Coverage: 5,000,000 companies
Best for: Startup selling, PLG companies, tech early adopters, competitive intelligence
Data Source: Product Hunt GraphQL API + Gemini 2.5 Pro analysis