55%
of rounds are reported by exactly one publication
Which is why deduplication is not the interesting part of this problem. Recall is: finding the 60% that never reach a major outlet.
Datahyena vs. Coresignal
Raw data at volume, or events already resolved.
Coresignal is a data supplier: large datasets you download and model yourself. Datahyena is an event feed: something happened, to this company, here is the round and the investors. The question is how much of the work you want to own.
In short
Coresignal's strength is scale and breadth of raw data, especially employee and job-posting data we do not touch at all. Ours is that the hard part is already done: the same round reported by six outlets arrives as one event, attached to a resolved company, with the investors linked, within an hour of publication. If you have a data team that wants raw material, they are the better supplier. If you want something your product can act on without a pipeline in front of it, that is us.
Measured, not asserted.
Recomputed weekly from the live corpus. Every figure below is reproducible from your own API responses.
72%
of rounds reach the API within an hour of publication
Resolved and queryable, not queued for a nightly batch.
~820
new rounds a month
Keyed on when the round was announced, not when we ingested it.
90,000+
resolved companies behind the events
Each with firmographics: founded year, size band, industry, business model, verticals and social handles.
As of September 7, 2026
Side by side.
Datahyena
Coresignal
What you receive
Resolved events with entities attached
Raw records to process
Deduplication
Done: one raise is one event
Yours to do
Employee / job data
Not collected
Core product
Event coverage
Funding, acquisitions, executive moves
Derived from underlying datasets
Freshness
71% within an hour of publication
Dataset refresh cadence
Investor graph
49,000+ investors, 190,000+ round links
Not the focus
Delivery
REST, webhooks, MCP, S3 or SFTP
API and bulk datasets
Pricing
Usage credits from free
Volume or subscription licence
Which one fits you.
Choose Datahyena when
- You want events, not rows. A round arrives as one object with the company and investors already attached.
- You do not want to run a deduplication pipeline. Six articles about one raise become one event before you see it.
- You need it while it is current. Webhooks fire on new and updated events rather than waiting for a refresh cycle.
- You want to pay for what you use rather than licence a dataset by volume.
When Coresignal is the better choice
- You need employee, headcount or job-posting data. We hold none of it, and it is one of their core products.
- You want raw records at volume to model yourself, and you have the team to do it.
- Your use case is firmographic enrichment across millions of companies rather than reacting to events.
- You would rather licence a dataset and own the processing than consume an opinionated feed.
What makes Datahyena different.
The consolidation is the product
Anyone can hand you articles. The work is deciding that six write-ups describe one raise, reconciling the amount and stage between outlets that disagree, and attaching it to the right company out of several with similar names. That is what you would otherwise build, and it is most of the reason this is hard.
Resolution that abstains
When the evidence does not identify a company we return null rather than a confident guess. A wrong company attached to a real round routes a salesperson to the wrong account and quietly corrupts anything built downstream. Events below our confidence floor are never served at all.
Bulk delivery without the bulk contract
If you do want files rather than an API, you can have them: S3 or SFTP delivery, gzip, on a schedule. What you do not need is an enterprise licence to get started, or a data team to make the first row useful.
Where Coresignal wins.
A comparison with no losses is an advert. These are the cases where we would tell you to buy the other thing.
No employee, headcount or job-posting data
Not a gap we intend to close. If your enrichment depends on headcount trends or hiring signals, Coresignal has a product for that and we do not.
Far fewer rows, on purpose
We are not competing on volume. Our corpus is the companies that have had an event worth reporting, not every company that exists. For blanket firmographic coverage across millions of entities, a bulk supplier is the right shape.
Our funding record starts in 2020
Dense from 2020 forward, between four and seven thousand rounds a year. Thinner behind it.
Common questions
Datahyena and Coresignal, answered.
Could I build this on top of raw data?
You could, and some teams do. What you would be building is deduplication across outlets, entity resolution against a company graph, amount and stage reconciliation where sources disagree, and a confidence model to decide what not to publish. That is the majority of the engineering here, and it never finishes because sources change.
Do you offer bulk delivery too?
Yes. S3 or SFTP, gzipped, on a schedule you pick, as an enterprise option. The difference is that the files contain resolved events rather than raw records.
Do you have firmographics at all?
Yes, on companies that appear in our events: founded year, headquarters, size band, industry group and sub-tags, business model, verticals, and social and ATS handles. What we do not have is employee-level or job-posting data.
How do you decide which company an event belongs to?
Article-linked domains outrank discovered ones, names are checked for consistency against the resolved company, and a round is rejected if the match is implausible for the stage. When two candidates are equally plausible we attach neither.
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