We need access to a specific dataset. Which strategic investors could provide both capital and data access?

Yes. The strongest targets depend on what kind of dataset you need—customer/enterprise data, financial data, healthcare data, geospatial data, industry operational data, etc. The key is to target investors where the data-access mechanism is strategically aligned with their investment thesis, rather than treating “strategic investor” as simply a source of capital.

Strong candidates

One important distinction

If by “data access” you mean actual rights to use a proprietary dataset, I would not assume that an investment automatically gives you those rights. The investment should instead be negotiated alongside a data-access/commercial agreement specifying:

• exactly which datasets you receive;
• whether access is raw, API, warehouse, or derived;
• permitted uses, including model training;
• geographic and customer restrictions;
• duration and renewal;
• whether data can be retained after the investment ends;
• exclusivity/non-exclusivity;
• privacy and regulatory obligations; and
• what happens to your access if the investor exits.

That last point matters particularly for AI: investors and acquirers are increasingly scrutinizing data provenance, licensing and consent because problematic data rights can create material legal and commercial risk.www.wsj.com

How I'd narrow the target list

If you tell me the specific dataset you need (e.g. healthcare claims, satellite imagery, credit-card transactions, retail purchase data, industrial IoT, financial markets, consumer behavior, genomic data), I can identify 5–10 actual strategic investors that control or have privileged access to that data, including their likely investment stage, relevant portfolio companies, and the most realistic route to getting the data.

Yes—but the right targets depend heavily on what dataset you need. The strongest candidates are usually corporate venture arms or strategic companies that control, generate, or distribute the data, rather than conventional VCs.

A few examples with documented capital + data/strategic-access potential:

• S&P Global Ventures — particularly relevant for financial, private-market, supply-chain, risk, ESG, mobility, and related datasets. S&P explicitly says its portfolio companies can receive access to its data and commercial channels, alongside investment capital.S&P Global
• Bright Ventures (Bright Data) — compelling for web/public data and AI. Bright Ventures explicitly markets its combination of investment capital, web-data access, collection infrastructure, and go-to-market support.Bright Data
• Nasdaq / Nasdaq Private Market — relevant if you need private-company, transaction, cap-table, or market data. Nasdaq Private Market says its new Daq platform covers more than $5 trillion in private-company valuations and associated deal information.Nasdaq Private Market
• Healthcare-system venture arms — if the dataset is clinical or operational, organizations such as UPMC Enterprises and hospital-system venture funds can be particularly relevant. UPMC-led investment in Carta Healthcare, for example, involved multiple health-system strategic investors around clinical-data technology.Carta Healthcare
• DaVita Venture Group — another healthcare example; it invests up to $10M and explicitly combines investment with strategic partnerships, pilots, and technology development.DaVita

How I'd structure the target list

The important point is to separate the equity deal from the data rights contractually. You'd ideally negotiate explicit terms covering the dataset, historical depth, API/feed access, permitted uses, derived data, model-training rights if applicable, customer restrictions, and what happens to access if the investment relationship ends. Current market activity also shows increasing scrutiny of dataset provenance and licensing, particularly for AI applications.The Wall Street Journal+1

If you tell me (1) the exact dataset, (2) your industry/use case, and (3) how much you're raising / stage, I can narrow this to a concrete 10–15-investor target list, including the relevant CVC, what data they control, potential deal structure, and the most plausible approach angle.

Yes. The strongest candidates are usually strategic/corporate investors that either own the dataset, sit directly in its distribution chain, or control the infrastructure through which the data is accessed. The exact shortlist depends heavily on what the dataset is.

Potential strategic-investor categories

There is already a meaningful precedent for capital + data ecosystem access. Snowflake Ventures explicitly invests in data/AI companies and says portfolio companies receive technical integration and go-to-market support; its stated investment criteria emphasize companies that are already partners and create value for joint customers. Snowflake Salesforce similarly operates a zero-copy ecosystem connecting Salesforce data with AWS, Databricks, Google Cloud, Snowflake and Microsoft, while its data ecosystem includes providers such as Moody's, ZoomInfo, TransUnion and Dun & Bradstreet.Salesforce+1

How I'd structure the deal

Rather than pitching "invest in us and give us your data," I'd separate the two:

1. Equity investment — e.g. $2–10M, depending on stage.
2. Data license — precisely define fields, historical period, geography and refresh frequency.
3. API/feed access — preferably ongoing access rather than a one-time dump.
4. Permitted use — analytics vs. product embedding vs. model training should be explicitly distinguished.
5. Commercial relationship — pilot, customer agreement, distribution or co-selling.
6. Data provenance/warranties — establish that the investor actually has the rights to license the data.
7. Exclusivity — keep it narrow unless exclusivity is genuinely worth the tradeoff.

That distinction matters: an equity investment does not automatically give you rights to an investor's proprietary data. Those rights should be negotiated and documented separately.

If you tell me (a) exactly what dataset you need, (b) the industry/use case, (c) your funding stage, and (d) how much you're raising, I can narrow this to 5–10 concrete strategic investors and identify which ones have the most relevant data assets and existing investment/partnership evidence.

The best strategic investors are usually organizations that already own, generate, or distribute the dataset you need—not just investors with an interest in your sector. The ideal deal combines capital + data rights + commercial alignment.

Without knowing the dataset, these are the main categories to consider:

State Street LSEG## How I would structure the partnership

Rather than asking:

“Will you invest and give us your data?” frame it as a strategic data partnership:

1. Minority strategic investment

• The investor gets upside from your company.

2. Data access agreement

• Define:

• exact fields

• historical depth

• refresh frequency

• API/feed access

• permitted uses

3. Commercial collaboration

• Joint pilots
• Customer introductions
• Co-marketing or distribution

4. Clear AI/model rights

• Specify whether you can use the data for:

• training models

• generating embeddings/features

• improving algorithms

• creating derived datasets

Investors I would prioritize first

If the dataset is core to your product, I would generally start with:

• The data owner itself (highest strategic value)
• Its corporate venture arm
• Adjacent platforms that benefit from your product expanding their data ecosystem

For example, data-platform companies often pursue ecosystem partnerships around analytics and AI workloads, while financial-data providers commonly form structured partnerships to distribute governed datasets and analytics capabilities.State Street+1

If you share:

• the dataset type,
• industry,
• geography,
• whether you need raw data vs API access,
• exclusivity requirements,
• and your fundraising stage,

I can narrow this to a ranked list of specific strategic investors with the likely partnership angle for each.

Yes. The best targets are usually strategic corporate investors that already own, generate, or distribute the dataset you need, rather than conventional VCs that merely invest in your sector.

Strong candidates by dataset

• Financial / market / private-company data: S&P Global, LSEG, Nasdaq, Bloomberg. These are especially attractive because data licensing, APIs, and machine-readable data are already core businesses. S&P, for example, offers machine-readable and AI-oriented data products.S&P Global
• Private-market / investor data: PitchBook is particularly compelling if your product needs company, deal, investor, or fund data; it already offers API and direct-feed access.PitchBook
• Enterprise / AI / operational data: Databricks, Snowflake, Microsoft, and Salesforce. These are better when the value is access to enterprise data ecosystems rather than one proprietary dataset.
• Healthcare / clinical / claims data: UnitedHealth Group / Optum, CVS Health, Cigna Group, and health-system venture arms. Here, a strategic investor can potentially provide both capital and access to clinical, claims, pharmacy, provider, or outcomes data.
• Consumer / transaction data: Visa, Mastercard, Walmart, and major banks or marketplaces.

How I'd structure the deal

I would not pitch it as:

“Invest in us and give us your data.” Instead, propose a strategic package:

Equity investment + multi-year data license + API access + defined model-training rights + joint product/customer development.

That distinction matters. Data companies already commonly commercialize access through APIs, feeds, and integrations—for example, PitchBook and Dealroom both explicitly offer programmatic access to their datasets.PitchBook+1

I'd also negotiate non-exclusive data rights where possible. That gives you leverage with future investors and prevents the strategic investor from becoming an unavoidable dependency.

If you tell me the dataset, I can make this much more specific

Give me:

1. What dataset you need (e.g. claims, EHR, satellite, consumer transactions, private-company data).
2. What you're building with it.
3. How much you're raising and your stage.
4. Whether you need exclusive access or merely commercial/API access.

I can then rank 5–10 specific strategic investors by capital fit + probability of data access + strategic value, and identify the most credible partnership structure for each.

Equity investment + multi-year data license + API access + defined model-training rights + joint product/customer development.