Calculate How Much My Data Is Worth →
The same data your company generates every day running its business, support tickets, internal communications, project histories, code repositories, CRM pipelines, could be worth anywhere from $20,000 to several million dollars to AI companies right now.
Most small and mid-sized businesses have no idea this market exists. The ones that do are quietly collecting five and six-figure checks from AI labs without changing how they operate at all.
This guide explains exactly how the market works, what your data is worth, which companies will buy it, and how to do it without putting your business or your customers at legal risk.
Quick reality check: AI labs have already paid over $10M for a single company's archives (Google's bid for Spirit Airlines' data). micro1 announced a $1 billion, 12-month commitment to buy operating records from businesses. This is a real market with real money moving through it.
Why AI Companies Are Paying Real Money for Business Data
Large language models and AI agents need training data that reflects how businesses actually operate, not just what appears in public text on the internet. The public web has largely been scraped. What AI labs are hunting for now is proprietary, real-world operational data that shows how decisions get made, how problems get resolved, and how work actually flows inside a company.
Your Slack threads showing how your team debugs a production issue are more valuable than a Stack Overflow post about the same topic, because they show the messy, real process, the wrong turns, the correction, the final solution. Your support ticket history is worth more than a generic FAQ because it shows real customer problems with real resolutions.
Three types of data are driving the most demand right now:
| Data Type | Why AI Labs Want It | Estimated Value Range |
|---|---|---|
| Internal communications (Slack, Teams, email) | Shows real reasoning, decision-making, and problem-solving in context | $316K median per company (SellMyData benchmark) |
| Code repositories with full history | Commits + issues + fixes + tests show real development process | $30K to $10M+ depending on complexity and history |
| Business records (CRM, support, ops) | Reflects real-world processes across diverse industries | $20K to $1.5M depending on volume and niche |
| Agent workflow traces | AI agents learning from recorded task completions | $200 to $2,000 per task set |
| Evaluation datasets | Test sets measuring AI behavior against known answers | Premium pricing; labs compete heavily for these |
| Documents (SOPs, contracts, playbooks) | Niche operational knowledge hard to find in public data | $50K to $500K+ for industry-specific archives |
What Actually Makes Your Data Worth More (or Less)
Volume is the last thing on the list. AI labs care about these factors in roughly this order:
- Linkage. Data that tells a story across systems is worth far more than isolated records. A bug ticket linked to the commit that fixed it, linked to the Slack thread debating the approach, linked to the test suite that verified it, is exponentially more valuable than any of those pieces alone.
- Scarcity. Data from niche industries (manufacturing, energy, insurance, logistics, healthcare operations) is worth more than generic office data. The rarer your industry context, the higher the premium.
- Clean rights. If you can prove you own the data cleanly, with no customer IP, no third-party licensed content, no unresolved contractor IP issues, you can close a deal faster and for more money. Rights problems are the number one reason deals fall apart.
- Exclusivity. Selling exclusive rights typically commands 4 to 5 times the non-exclusive price. Many buyers will pay significantly more for a dataset that only they will have access to.
- History. Longer continuous histories are worth more. A codebase with 10 years of history is worth more than one that started last year. Five or more years of operational data is considered premium.
- Language and system. For code, low-level languages (Rust, Go, C, C++) from complex production systems command higher prices than commodity web code.
Warning: AI lab estimator tools can vary by up to 20x for the same dataset. Do not treat one buyer's estimate as a definitive value. Get multiple estimates before accepting any offer.
What You Can Legally Sell (and What You Absolutely Cannot)
This is where most businesses get into trouble. The fact that data exists in your systems does not mean you own it or have the right to sell it. Here is an honest breakdown:
Generally Safe to Sell
| Data Type | Why It's Usually Sellable |
|---|---|
| Your own SOPs, playbooks, and internal documentation | Your company created it, your company owns it |
| Code your employees wrote as part of their job | Usually covered by employment IP assignment agreements |
| Your internal project management and ticket history (with client names removed) | Your work process, not client IP |
| Your sales process documentation (not client data) | Internal operational knowledge |
| Financial and operations records with identifiers stripped | Operational data, not personal data |
| Your email and Slack threads about internal decisions | Internal communications about your own operations |
High Risk or Cannot Sell
STOP: Never sell these without detailed legal review.
- Client work product covered by an NDA or service agreement. If you built something for a client and your contract says their materials are confidential, you cannot sell records of that work.
- Customer data or personal information. Even if it's in your CRM, your customers' contact and transaction data is typically protected by privacy laws and your own privacy policy.
- Third-party licensed content. If your documentation includes licensed templates, vendor materials, or open-source code with restrictive licenses, those cannot be relicensed to AI labs.
- Contractor-created IP without assignment. If a contractor built something for you and there was no written IP assignment agreement, they may still own the copyright.
- Data from SaaS platforms where you are the customer. Your Salesforce data may be covered by Salesforce's terms of service in ways that restrict what you can do with it.
Which Platforms and Buyers Are Actively Purchasing Business Data
The market has matured quickly. There are now dedicated platforms, brokers, and direct buyer programs from AI labs. Here is what each one is best suited for:
Marketplaces and Platforms
| Platform | Best For | Typical Range | How It Works |
|---|---|---|---|
| SellMyData | Internal business records (Slack, email, documents, code) | Based on team size + data depth | Answer questions, export data via their tool, approve the redacted listing, get paid within 7 days of sale |
| DataVendor | Codebases with history, raw data ZIPs, evaluation task sets | $30K+ per codebase (floor); some exceed $10M | Publish a listing or register in Inventory; labs browse and purchase; structured quality checks before listing goes live |
| Defined.ai | Enterprise-grade data with compliance requirements (GDPR, ISO 27001) | Custom, enterprise pricing | Formal intake process with consent framework; suited for regulated industries |
| Opendatabay | Public listings of commercially licensed training data | Varies widely by modality and size | Open marketplace model; set your own price; broader buyer exposure |
Direct Buyer Programs
| Buyer | Stated Pay Range | Minimum Size | Notable Details |
|---|---|---|---|
| micro1 | $100K to $3M+ tiers | 30+ full-time employees | Data partnerships program; payment within 30 days of invoice; may rewrite some data synthetically |
| Handshake AI | $100K to $4M+ | 20+ full-time, 3+ years operating | NDA-first process; scope and terms agreed before you share anything |
| Mercor | $20K to $1.5M | No published floor | Covers extraction and anonymization costs; wire payment in 2 to 4 weeks after signing |
| Scale AI | $10K to $1M+ (illustrative) | 40+ preferred | Anonymizes inside your environment before extraction; ongoing partnership model |
| Labelbox Prism | $50K to $1M+ | No published floor | Upfront fee at signing plus revenue share; default to exclusive deals |
| Polyshares | $100K to $2M+ | No published floor | Published deals from $110K to $450K; non-exclusive by default; no seller fees |
| Troveo | Six figures+ (revenue share) | No published floor | Revenue share per sale; brokers your data to multiple buyers |
| Endless Data | Up to $4M (fixed sum) | Roughly 30+ | Non-exclusive; fixed sum agreed before you share anything; no seller fees |
| SimpleClosure AssetHub | $10K to $100K+ (press) | Any operating or closing startup | Targets companies closing or winding down; takes a success percentage |
Best path for most small businesses: Start with SellMyData or Mercor for internal business records. For codebases with 5+ years of history, check DataVendor. For higher-value deals, run a parallel process with Handshake AI and Endless Data to get competing offers.
Step-by-Step: How to Sell Your Business Data to an AI Company
Here is the actual process from first evaluation to payment in your account:
Step 1: Take Inventory of What You Have
Before approaching any buyer, map your data assets. For each system your company uses, ask: how many years of history does it contain? Who created the data (employees, contractors, customers, third parties)? Is any of it covered by an NDA, customer contract, or third-party license?
The highest-value assets are typically: internal communications showing decision-making (Slack, Teams), code repositories with full commit history, support ticket systems showing problem-resolution patterns, operational documentation (SOPs, runbooks, playbooks), and CRM pipeline histories with contacts stripped.
Step 2: Get Multiple Value Estimates
Use the estimator tools from SellMyData and DataVendor as a starting point, then contact two or three direct buyers for a ballpark range. Because estimates can vary by up to 20x, the only way to know your real market value is to run a parallel process with multiple buyers.
When estimating, describe your data by: linked systems (not just individual data types), years of continuous history, your industry and niche, approximate record volumes, and the percentage that is unique versus commodity data.
Step 3: Do a Rights Audit
Before any buyer sees a sample, resolve your rights questions. The key questions: Do your employee contracts include IP assignment clauses? Do any client contracts include confidentiality provisions that cover the data you want to sell? Are there third-party licenses embedded in your content? Do your SaaS vendor agreements restrict data export or resale?
If you have any uncertainty, get a qualified legal opinion before proceeding. A rights problem that surfaces mid-deal can kill it, and some deals require representations and warranties about ownership that expose you to liability if they're wrong.
Step 4: Prepare and Anonymize Your Data
Different buyers handle anonymization differently. Some (like Mercor and Scale AI) handle the scrub themselves and do not want you to touch the data first. Others expect you to deliver a clean, de-identified export. Confirm the buyer's preference before you start preparing anything.
If you are preparing it yourself, the standard approach is: remove direct identifiers (names, email addresses, phone numbers, account numbers), review for indirect identifiers that could allow re-identification when combined, strip old commits and attachments for embedded credentials or customer details (not just the latest version), and prepare a separate delivery copy, leaving the original archive untouched.
Important: removing names is usually not enough. UK ICO guidance and similar frameworks note that remaining details can often still identify individuals. For anything involving personal data, verify your anonymization approach against the relevant privacy framework for your jurisdiction.
Step 5: Run a Parallel Negotiation Process
Do not accept the first offer. The buyers in this market expect you to shop the deal. Run at least two or three conversations simultaneously. For higher-value datasets, a broker like Troveo can run a formal sale process and create competitive tension between buyers.
Key terms to negotiate beyond the headline price: exclusivity (or lack of it), payment timing, what the buyer can do with the data after purchase (permitted uses), how long they can retain it, and what representations you are making about the data's rights status.
Step 6: Review and Execute the Agreement
Before signing anything, have a qualified attorney review the data licensing agreement. The specific provisions that matter most: the scope of the license being granted, representations and warranties about ownership and accuracy, indemnification language (who is responsible if there is a rights problem discovered later), data retention and deletion provisions, and any restrictions on your future use or sale of the same data.
Step 7: Deliver, Approve, and Get Paid
Payment timing varies by buyer. SellMyData targets 7 days after a sale closes. Mercor wires within 2 to 4 weeks of signing. micro1 has up to 30 days to review and then 30 days to pay after invoice. Get the payment timeline in writing before signing, and confirm what triggers the payment clock (delivery, acceptance, or signing).
Pro tip: Silence can count as acceptance. micro1's terms allow 30 business days to reject, and silence counts as acceptance after that window. Know your contract terms before delivery.
What AI Training Data Is Actually Worth: A Pricing Reference
Published deal data and marketplace benchmarks give you a realistic starting point for understanding what different types of data trade for. These are actual market figures, not estimates:
| Data Type | Format / Basis | Published Range / Median |
|---|---|---|
| Company business records (Slack, email, docs, CRM) | Per company license | $316K median; deals from $20K to $4M+ |
| Text archives (licenses of large text collections) | Per contract year | $16M median per contract year (major archives) |
| Books and written works | Per title | $3,000 per book or title (median) |
| Codebase with history | Per repository | $5K baseline (small/private); $30K floor (quality); $10M+ (top-tier) |
| Speech / audio data | Per hour of audio | $118 per hour (existing); $24 per hour (recorded to order) |
| Video footage | Per hour of video | $42 per hour (existing); $95 per hour (creator-owned) |
| Images | Per image | $0.098 per image (median) |
| RL training task + grader | Per task set | $200 to $2,000 per task |
| Exclusive rights premium | Multiplier on base price | 4x to 5x the non-exclusive price |
Real deal anchors: Google bid $10M for Spirit Airlines' archive (a rival offered $12.5M). A single closed company's archive: mid-six figures. A startup's failed codebase: tens of thousands. A production Rust codebase with 10+ years of history: could exceed $1M.
The Legal Reality: What to Get Right Before You Sign Anything
The legal side of selling business data is more complicated than the platforms make it sound. Here are the issues that most commonly create problems:
Employee IP Assignment
If your employees wrote the code or created the documentation you are selling, do your employment contracts include IP assignment clauses that transfer those rights to the company? In many jurisdictions, work created by employees in the course of their employment belongs to the employer, but this is not universal and is not always clean-cut for work done partially outside of normal hours or on personal equipment.
Contractor IP
Contractors are the most common rights problem in data deals. Unless a contractor signed an explicit IP assignment agreement (not just a work-for-hire clause, which has jurisdiction-specific limitations), the copyright in their work may still belong to them. If your codebase includes contractor contributions from the last several years without signed assignments, resolve this before approaching buyers.
Customer Contracts and NDAs
Read your customer contracts carefully. Many service agreements include confidentiality provisions that cover the work product and communications generated during the engagement. Even if the data has been de-identified, if it relates to a client project, you may be in breach of contract by licensing it to a third party.
Privacy Laws
GDPR (if you have EU customers or employees), CCPA/CPRA (if you have California customers), and similar laws may apply to data you hold. These frameworks do not automatically prohibit selling de-identified data, but they impose requirements on the de-identification process and may require that your privacy policy disclosed the possibility of such use at the time the data was collected.
California's AB 2013 specifically addresses personal data used in AI training inputs. If your data includes personal information about California residents, that law may require additional disclosures or impose other requirements.
SaaS Vendor Terms
Many SaaS vendors include provisions in their terms of service that restrict what you can do with data generated through their platform. Salesforce, HubSpot, Slack, and others have terms that may restrict data export, resale, or use in ways that could affect an AI data deal. Review the terms of service for any platform from which you plan to export data before signing a licensing agreement.
Legal bottom line: Get a qualified attorney to review any data licensing agreement before signing. The representations and warranties in these deals can expose you to liability if rights problems surface after payment. The cost of legal review is typically a small fraction of the deal value.
Is Selling Your Data Right for Your Business?
Selling your business data is not the right move for every company. Here is an honest framework for deciding:
| Good candidate if... | Less ideal if... |
|---|---|
| You have 5+ years of operational history | You are under 3 years old with limited operational depth |
| You operate in a niche or specialized industry | You handle sensitive regulated data (healthcare, financial, legal) with complex compliance requirements |
| Your team is 20+ people (more data depth) | Your service agreements broadly cover all work product as confidential |
| Your employment contracts include IP assignment | You have significant contractor contributions without signed IP assignments |
| You have clean customer contracts with no broad confidentiality clauses | Your business involves processing customer personal data as a core function |
| You are comfortable with a one-time or time-limited license deal | Your SaaS vendor agreements restrict data export or resale |
| Your business data reflects complex, real-world problem-solving |
Frequently Asked Questions
Will my customers find out I sold data about them?
If the process is done correctly, buyers receive de-identified data with no customer names, contacts, or identifiers. Your customers are not being sold. What is sold is anonymized operational data showing patterns and processes. That said, your privacy policy should accurately describe your data practices, and if it does not currently contemplate data licensing, you may want to update it going forward.
Can I sell data from a company that is winding down or closing?
Yes, and this is an emerging area. Platforms like SimpleClosure AssetHub specifically target companies that are closing. Closing companies can sell their historical data as part of the wind-down process. The same rights questions apply, and the process is typically faster since there is urgency on both sides.
Can I sell the same data to multiple buyers?
It depends on the license structure. Non-exclusive licenses allow you to sell to multiple buyers, but each buyer will pay less than they would for exclusivity. Exclusive licenses command 4 to 5 times the price but are sold to only one buyer. Some buyers (Endless Data, Polyshares) default to non-exclusive. Others (Labelbox Prism) default to exclusive. This is negotiable in most cases.
How long does the process take from first contact to payment?
Expect 4 to 12 weeks from first contact to payment for most deals. The timeline depends on how prepared your rights documentation is, how quickly you can prepare a data sample, the buyer's review and acceptance process, and payment timing after acceptance. Deals with rights complications can take longer. Having a clean rights file ready before you start significantly compresses the timeline.
What happens if the buyer discovers a rights problem after they have paid?
This depends entirely on the representations and warranties in your agreement. Most data licensing agreements include a right to seek damages or clawback provisions if the seller's representations about data ownership turn out to be false. This is precisely why legal review of the agreement and a thorough pre-sale rights audit are important.
Is the income from selling data taxable?
Yes. Revenue from data licensing is ordinary business income and is taxable in the year received. For large one-time payments, there may be installment payment structures or other arrangements worth discussing with a tax advisor before signing. Keep records of the sale and any related expenses.
Bottom Line
There is a real, active market for business operational data, and it is significantly larger than most business owners realize. AI labs are spending tens of millions of dollars acquiring the kind of proprietary, real-world data that cannot be found anywhere on the public internet, and the data your company generates every day running its operations may be exactly what they need.
The most important thing to do before approaching any buyer is to understand what you actually own. Run the rights audit, check your customer contracts and SaaS vendor terms, make sure your employment agreements include IP assignment, and confirm your anonymization approach is solid. The deals that fall apart do so because of rights problems, not because the data was not valuable.
For most established businesses with 5 or more years of operational history in a specialized field, the market value of your data is higher than you expect. The floor for a quality dataset is typically $20,000 to $50,000, and six-figure and seven-figure deals are common for companies with deep operational archives.
Use the AI data value calculator to get an initial estimate, then start conversations with two or three buyers simultaneously to get a real sense of your market value.
About American Business Center: American Business Center provides trusted, plain-English guides, reviews, and tools for U.S. small and mid-sized business owners. This article is for informational purposes only and does not constitute legal, financial, or tax advice.