PitchBook alternatives for tracking private company momentum

A private company leaves two trails. One is capital: who invested, in which deal, from which fund. The other is operations: the roles it opens, the countries it starts selling in, the tools it adopts, what it announces. PitchBook follows the first. Fokals delivers the second, with every observation dated, for the months between financing events.

This guide describes what PitchBook covers and what it is built for, lists other databases for the capital trail, and works through a momentum screen you can run on a watchlist of private companies. PitchBook is described here from the 2025 annual report of Morningstar, its owner, and from a PitchBook press release, read on 4 October 2026. Fokals is delivered direct, by REST API and as bulk files, which you load into your own systems.

What PitchBook covers

Morningstar's 2025 annual report says PitchBook gives investors access to a collection of private market data and insights, complemented by Morningstar's data and research on public equities. According to the report, its data covers private and public companies, investors, funds, deals, loans and executives, and a research team publishes on private equity, venture capital, credit, M&A and managed vehicles.

The report also describes the product a client works in. In the PitchBook platform it lists search, market dashboards, benchmarking, analytics of fund performance and portfolio monitoring. Data reaches other tools through mobile applications, CRM integrations, Excel and PowerPoint plug-ins and integrations with enterprise AI providers, and direct data products supply it by API and data feed. Its clients, the report says, include private equity and venture capital firms, asset managers, limited partners, investment banks, private credit investors, corporations and professional service providers.

On licensing, the report says the platform is priced mainly by the number of licensed users, and direct data products by the volume of data, how often it is refreshed and the technical specification.

A PitchBook press release of February 2026 adds two facts. It announced Valuation Estimates, a model-based valuation for venture-backed companies that it says is refreshed daily and built into the platform, and it states that PitchBook was founded in 2007 and has operated as a subsidiary of Morningstar since 2016.

What PitchBook is built for

A deal and fund database is the tool for work of these kinds.

• Finding the deals a company has done and the investors and funds behind them.
• Benchmarking, and analysing the performance of funds.
• Reading analyst research on private equity, venture capital, credit and M&A.
• Reading a model-based valuation estimate for a venture-backed company.
• Working in Excel, PowerPoint or a CRM fed by plug-ins and integrations.

The operating trail is a different record: what each company on a watchlist did this week and this month, as dated rows that a model, a warehouse or a memo can use. That is the record Fokals delivers, and the rest of this guide works with it.

Why a team adds or looks for another source

• A different kind of data. Financing events are months or years apart. Between them the question is whether the company is still building, and the answer shows in what it does, not in who holds its shares.
• Delivery. The data is going into a model, a warehouse or a product, so the need is rows by API or file under a licence that names that use. PitchBook's direct data products and a signals feed are both candidates, for different rows.
• Scope. The team needs one narrow thing, such as hiring momentum on the 300 companies in its portfolio and pipeline, and wants to license that alone.
• Licence fit. The output is embedded in a product or passed on to clients, and the agreement has to say so.

PitchBook and Fokals side by side

Each cell restates what is said publicly about the vendor's scope, sources, delivery and licensing: for PitchBook, in its owner's annual report and one of its press releases.

A momentum screen from dated operating signals

The screen asks one question of each company on a watchlist: over the last four weeks, did it do more or less than before? Every dataset and field below is specified in the data dictionary.

1. Resolve the watchlist. Match each company's website domain to the Fokals company index. Each domain resolves to the stable company ID that every dataset carries.
2. Hiring. From Hiring Activity, in the hiring dataset, take open postings on the latest closed day and the sums of new and closed postings over 28 days. Net new postings divided by open postings compares a company with 12 open roles to one with 400, and the breakdown by job function shows whether the growth is in engineering, sales or operations.
3. Commercial build-out. From Sales Team Metrics, read open sales roles, new countries and the first enterprise-segment role. A first sales posting in a new country, or a first enterprise-segment role, is a dated statement of where the company intends to sell.
4. Product and stack. From Technology Changes, count events by kind: a tool adopted or removed, a platform migration, a new market, a pricing or demo page added.
5. What the company says. From Company News, read the event types: product launch, partnership, expansion, funding round, leadership change, layoffs and restructuring.
6. The capital trace. From Company Funding, read any private capital raise reported in a regulatory filing: its filing date and the amount sold. It is the one point where this trail touches the other.

The query below runs steps 1, 2 and 4 over the 28 days to the latest closed day.

with ids as (
  select distinct w.domain, t.company_id
  from my_watchlist w
  join company_technologies t on t.domain = w.domain
),
hiring as (
  select
    company_id,
    max(case when day = :as_of then open_postings end) as open_now,
    sum(new_postings) as new_28d,
    sum(closed_postings) as closed_28d
  from company_hiring_daily
  where day between :from_day and :as_of
  group by company_id
),
changes as (
  select company_id, count(*) as site_changes_28d
  from company_tech_events
  where observed_at >= :from_day
    and category in ('technology', 'platform', 'market', 'page')
  group by company_id
)
select
  i.domain,
  h.open_now,
  h.new_28d - h.closed_28d as net_new_28d,
  round(1.0 * (h.new_28d - h.closed_28d) / nullif(h.open_now, 0), 2) as net_new_per_open,
  c.site_changes_28d
from ids i
left join hiring h on h.company_id = i.company_id
left join changes c on c.company_id = i.company_id
order by net_new_per_open desc nulls last;

Acme Robotics, an illustrative company with 40 open postings, 18 opened and 6 closed in the window, scores 0.3: it added roles equal to 30 percent of its open book in four weeks. Read each result against the checks below before it goes into a memo.

Reading the screen

Three properties of the record belong in any memo that uses the screen. Every observation is dated, and daily and weekly datasets are written once after the period closes and never revised, so the screen run as of any day it covers returns what was known that day. A first observation sets a baseline and is never counted as a change, so every new posting and every adoption in the screen is a true event. And a posting records an intention to hire, which is why the screen divides by a company's own open postings and compares each company with its own past.

Used beside a deal database, the screen fills the months between rounds. The guides to portfolio company monitoring for private equity and sourcing private companies for venture capital build on the same datasets, and the page for investors sets out identifiers and point-in-time design.

Other databases for deals, funds and investors

None of these was tested for this guide: each line says only what the vendor states on its own site.

• Preqin. Preqin, which presents itself as a part of BlackRock, describes private markets data on investors, funds, fund performance, fund terms and service providers, across private equity, venture capital, hedge funds, real estate, private credit, infrastructure, secondaries and natural resources, and a platform, Preqin Pro, for accessing private capital and hedge fund datasets and analytics tools.
• Crunchbase. Crunchbase documents company profiles with round history, valuations and investor details, and predictions of funding rounds, exits and growth. The guide to Crunchbase alternatives covers it.
• CB Insights. CB Insights describes APIs and data feeds with profiles of private companies, public companies and investors, funding deals, cap table history, M&A and IPOs.
• Dealroom. Dealroom describes data on startups, their founders and their funding, used by investors, corporates and governments, and offers an API in early access.

Choosing by the question

Frequently asked questions

The queries and code on this page are examples to adapt. Test them in your own environment before you rely on them.

What this page says about the products it names was checked against their public documentation on 4 October 2026. Product and company names are trademarks of their owners. Fokals is not affiliated with them or endorsed by them.