72%
of rounds reach the API within an hour of publication
From the article's publish timestamp to queryable, across 2,000+ served rounds.
Datahyena vs. Specter
A workspace to explore in, or an endpoint to call.
Specter gives a person a place to hunt: many signal types, filters, lists, exports. Datahyena gives a system something to react to: three event types, resolved, delivered by webhook. The right answer depends on whether a human or a program is at the other end.
In short
Specter covers a wider spread of signals than we do — headcount movement, web and social traction, hiring — and wraps them in a workspace built for hands-on prospecting. We cover funding, acquisitions and executive moves, go deeper on those three, and deliver them as an API and webhook with the latency published. If a person is doing the work, a workspace usually wins. If a program is, an endpoint usually does.
Measured, not asserted.
Recomputed weekly from the live corpus. Every figure below is reproducible from your own API responses.
55%
of rounds are reported by exactly one publication
Breadth of sources read is what decides recall, whatever the interface on top looks like.
36 minutes
median publication to API
84% are through inside two hours. Recomputed weekly from the live corpus.
45,000+
funding rounds, deduplicated and resolved
Plus acquisitions and executive moves against the same company graph.
As of September 7, 2026
Side by side.
Datahyena
Specter
Intended user
A program
A person
Signal breadth
Three event types, deep
Many signal types, broad
Growth signals
Not collected
Headcount, web, social traction
Detection latency
Published: 71% within 1h, median 36 min
Not published as a metric
Delivery
REST, webhooks, MCP, S3 or SFTP
Web app, exports, integrations
Agent access
Native MCP server
Not MCP-native
Per-company history
Timeline endpoint, one call
Company profile in the app
Pricing
Usage credits from free
Subscription tiers
Which one fits you.
Choose Datahyena when
- The consumer is code. Events arrive by webhook into your CRM, model or agent without anyone opening a tab.
- You want depth on the three events that trigger real action rather than breadth across many weak ones.
- You need the latency quantified. Ours is on this page and moves with the corpus.
- You would rather pay per use than per seat, and start on a free tier.
When Specter is the better choice
- You want signal types we do not carry: headcount trends, web traffic, app or social traction, hiring velocity.
- Your team prospects by hand, building and refining lists inside a tool.
- You want exports and no-code integrations rather than an API contract.
- Breadth of weak signals matters more to you than depth on a few strong ones.
What makes Datahyena different.
Depth on the events that actually trigger something
Headcount ticking up is weak evidence. A closed Series B with named investors is not. We would rather be the best available source for the three events that reliably change what a team does than a broad dashboard of things that might mean something.
Nothing to open
There is no workspace because the intended user is a system. Events arrive by webhook, an agent can query over MCP, and the whole corpus can be delivered as files if that suits you better. The dashboard exists for keys, usage and watchlists, not for browsing.
Latency published, not implied
Every product in this category says real-time. The measurable version is the gap between an article going live and the event being queryable. Ours is above, recomputed weekly, reproducible from your own responses.
Where Specter wins.
A comparison with no losses is an advert. These are the cases where we would tell you to buy the other thing.
No growth or traction signals
No headcount trends, web traffic, app rankings or social movement. Specter carries these and we carry none of them. If your scoring model runs on traction rather than events, we are not the input you need.
No prospecting workspace
No lists to build, no filters to save, no exports for a person to work through. There is a query playground and an API. For a team whose daily job is hands-on prospecting, that is a genuine mismatch.
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 Specter, answered.
Can I use this without writing code?
Partly. The dashboard has a query playground for running real requests and seeing real responses, and webhooks can point at a no-code tool. But there is no list-building interface, and if nobody on your team writes code you will get more out of a workspace product.
Why only three event types?
Because they are the ones that reliably change what a team does next, and because breadth is easy to add and hard to keep good. We would rather have the best funding coverage available than an adequate version of ten signal types.
What does the MCP server give me?
An agent can query funding events, resolve companies and read a company timeline as native tools, with no integration to build. Same credit accounting as the REST API.
How do you avoid the same round appearing twice?
Signals consolidate into one event: amount, stage and date reconcile across every outlet that reported it, and the event records how many independent publications it was seen in so you can weight corroboration.
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