A company-signal data API covering job openings, news events, technologies, funding and company relationships, delivered through REST, webhooks, flat files or MCP rather than a user interface.
What is
PredictLeads
PredictLeads has been logging company signals since 2016 and now holds over 9 million categorized news events, 270 million job postings and 244 million company-to-company connections. It sells that as a data feed rather than an app, so what you get is an API key and a set of company-level datasets. Eight separate datasets are behind that one key. News events pull from 20 million media sources and land in 37 categories, job openings refresh every 36 hours across 2.7 million companies, and technographics span 54,000 technologies. Key Customers is the unusual one, mapping 244 million vendor and client relationships by reading logo walls and case study pages. Delivery is where the API-first shape shows. You hit REST endpoints, follow a company for webhooks when it hires or raises, take flat files into S3 or BigQuery, or point an MCP server at it. There is no prospecting screen for a rep and no contact records in the product. PredictLeads earns its place once you already have somewhere to put it, which for most clients means Clay or a warehouse. Hiring, funding and technology moves are exactly the shape of signal we build triggers on. We have not used it directly at Nebor, and bought without a destination it becomes a good feed nobody reads.
Integrations and the modern GTM stack
PredictLeads has no application of its own, so the integration list is really a list of places you can land the data. The split worth understanding is between the automation tools that pull a company at a time and the bulk delivery routes that dump whole datasets into storage you control.
Clay | Five native actions cover Find Most Recent News, Find Open Jobs, Find Tech Stack, Find Financing Events and Find Connections. You can use Clay credits for them or connect your own PredictLeads key, and the second option is the cheaper one once volume climbs. This is the route we would take for anyone who wants the signal in a table today. |
Webhooks and followed companies | Follow a company for 1 credit a month and PredictLeads pushes events to your endpoint when that company hires, raises, launches a product or picks up a new technology. Webhooks trigger on job openings, technology detections, news events and connections, and this is the mechanism that turns the dataset into a real trigger rather than a lookup. |
Flat files to S3, GCS and SFTP | The enterprise route delivers full datasets in JSONL with point-in-time history back to 2015 and delta exports so you only process what changed. Priced separately from API credits and gated behind a demo, this is how you get the data into Snowflake or BigQuery for scoring rather than one-off enrichment. |
MCP server | An official MCP server with OAuth2 and header authentication lets Claude, ChatGPT or a custom agent query the datasets directly in a research loop. Listed on Smithery, PulseMCP and MCP Market. This is the newest surface and the one the vendor is clearly building toward. |
n8n, Make, Pipedream and ActivePieces | Native nodes and modules in all four, so you can build a signal-to-CRM workflow without writing a client. n8n is the one we see most in client stacks, and it pairs well with the webhook approach because the trigger arrives already structured. |
Apify and Cargo | Apify hosts a PredictLeads Actor for batch company enrichment, which suits a one-off list build better than a standing subscription. Cargo, Deepline and Oxygen wire the same signals into agent-driven GTM workflows for teams building on top of the feed. |
Polytomic | The only reverse ETL partner listed, syncing PredictLeads data from your warehouse into Salesforce or HubSpot. Worth noting because it exists to solve a gap: there is no direct CRM connector, so the warehouse has to be the middle layer. |
Data marketplaces | Listed on Datarade, Neudata, Nomad Data, Eagle Alpha, Databricks, Google Cloud, BigQuery and SAP Datasphere. Useful if your procurement already goes through one of those, and the Databricks and BigQuery listings save an ingestion step for data teams. |
What is missing | No native Salesforce or HubSpot connector, no Zapier app, no Instantly or Smartlead link, and no user interface for a rep to search in. Every path to a human passes through a tool you already own, so budget the destination before you budget the data. |
Pro’s
Job openings come off company career pages and refresh every 36 hours, so a hiring trigger lands while the role is still live rather than a week after the posting closed.
News events land pre-categorized into 37 types across 195 countries, so you filter for the three signals your buyers respond to instead of parsing raw headlines yourself.
The Key Customers dataset maps 244 million vendor, investor and client relationships read off logo walls and case study pages, and we have not seen that sourcing method anywhere else at this scale.
Pay-as-you-go starts at a $40 monthly minimum and falls to $0.002 a credit above 500,000 calls, so you can prove the data works before any annual commitment exists.
Every technology detection carries a score and the sources behind it, and a rep who can see the signal came from a DNS record rather than a job ad will trust the trigger more.
One key covers REST, webhooks, flat files into S3 or BigQuery and an MCP server, so the same feed reaches a Clay table and a warehouse without adding a second vendor.
Cons
It ships as a feed with no interface, so nobody on your team can look a company up. You need Clay, a warehouse or an engineer between the API and the person writing the email.
Credits expire at the end of every billing period with no rollover, so a quiet month of enrichment is budget you paid for and never used.
Discovery and Similar Companies endpoints bill per company returned rather than per request, and every extra page of results costs another credit, so a broad list build climbs well past the headline rate.
There is no people data anywhere in it, no contacts, no emails and no phone numbers, so PredictLeads gets you to the account and you still pay another vendor for the human.
PredictLeads puts flat file delivery at $24,000 to $150,000 per dataset in its own published comparison, so warehouse access is a very different conversation from the $40 you start on.
Pricing
Free
$0/month 100 API credits a month, no card required
Up to 100 API calls per month
Access to all datasets
REST API and webhooks
Enough to test data quality on your own accounts
101 to 5,000 credits
$0.04/credit $40 minimum monthly charge
Pay only for what you use
1 credit per API request, up to 1,000 records returned
Followed companies billed 1 credit per month each
No contract or commitment
5,001 to 10,000 credits
$0.02/credit Priority support included
Half the per-credit rate of the entry tier
Priority support
Same dataset access as every other tier
10,001 to 500,000 credits
$0.01 to $0.004/credit 24/7 support, rate drops at 100,001 credits
$0.01 per credit from 10,001 to 100,000
$0.004 per credit from 100,001 to 500,000
24/7 support
500,001+ credits
$0.002/credit Cheapest self-serve rate, contact them above this
$0.002 per credit at volume
24/7 support
Still self-serve with no annual contract
How it fits your stack
Alternatives
At a glance
120M+ company records, 2.4M with news coverage
9.8M active job openings, refreshed every 36 hours
37 news event categories from 20M+ media sources
54K technologies tracked across 86M companies
244M company connections from logos and case studies
REST API, webhooks, flat files and an MCP server
Native Clay, n8n, Make, Apify and Pipedream apps
100 free API credits a month, no commitment
Read some of our client stories
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