Slack, Microsoft Teams, Google Chat, Zoom
Chat & messaging
Message threads, handoffs, and meeting context.
Make Your Business DataWork as Hard as You Do.
Your team creates valuable knowledge every day. Rancher helps you turn it into licensed datasets for AI labs—and a new revenue opportunity for your business.
Already in your businessConversations. Decisions. Know-how.
A new use for existing dataFrom everyday work → AI progress
Built around your business. Not the other way around.
✓You define the scope✓You approve the terms✓You retain ownership
The opportunity
The next frontier of AI
is everyday expertise.
The internet shows AI what people say.
Your workflows show it how work gets done.
A resolved support ticket. A project that moved from idea to delivery. A decision with its context intact. These records can help AI labs train and evaluate models on real business tasks.
Rancher helps you explore that opportunity: identify useful data, prepare it responsibly, and structure a license that makes sense for your business.
What could your
data be worth?
Estimated payout range
$383,083—$896,969
A starting point for a conversation. Not a quote or guaranteed earnings.
20200+
3 years20+ years
Ordinary records.
Extraordinary context.
How your team works together.
The conversations behind the outcome: how teams coordinate, navigate ambiguity, and move work forward.
Message threadsEmail exchangesMeeting transcripts
THE POTENTIAL SIGNAL
Multi-step collaboration, decisions in context, and the path from question to resolution.
Examples of data to assess—not a request for unrestricted access. Eligibility depends on your rights, sensitivity, quality, and buyer needs.
Every system holds
part of your story.
Explore the records behind everyday work—and the AI capabilities they could help train or evaluate.
Gmail, Outlook, Google Calendar
Email & calendar
Email exchanges, scheduling, and linked follow-ups.
Google Drive, OneDrive, SharePoint, Dropbox
Documents & files
Documents, versions, authorship, and related files.
Jira, Linear, Asana, Monday.com, Notion, Figma
Work & knowledge
Tasks, specifications, design iterations, and project histories.
Salesforce, HubSpot, Google Calendar, Intercom, Zendesk
CRM, sales & support
Opportunity histories, service conversations, and resolutions.
ServiceNow, Workday, SAP, Microsoft Dynamics
Business platforms
Operational tickets, approved workflows, and process records.
QuickBooks, Stripe, NetSuite, Pigment, Shopify
Finance & operations
Invoices, reconciliations, order histories, and ledgers.
GitHub, Snowflake, Databricks, GitLab
Data & code
Repositories, issues, schemas, and documented changes.
Your own ecosystem
Internal & custom systems
Homegrown tools can hold distinctive workflows, specialized knowledge, and decisions that don’t exist anywhere else.
Tell us about your stackPlatforms shown are examples of potential data sources, not connected integrations, customers, or endorsements. All marks belong to their respective owners. Eligibility and licensing rights must be reviewed; use cases are illustrative.
From discovery to delivery
A clear path.
No leap of faith.
A hands-on partnership, with the scope and commercial terms agreed before any data is licensed.
01 /
Find the opportunity
Map your systems, data history, and licensing rights. Identify where your records could fit AI training or evaluation needs.
02 /
Set your boundaries
Define what’s included, what stays out, permitted uses, and the commercial structure. Review the proposed license before moving forward.
03 /
Prepare with care
Agree on a transfer method, remove or transform sensitive fields, and check dataset quality against the approved scope.
04 /
License. Earn. Repeat.
Deliver under signed terms and receive payment as agreed. Explore future licenses or updates only where your agreement permits.
Your data. Your boundaries.
Value shouldn’t come
at the cost of control.
Good data partnerships start with clear permissions. Build the scope, handling requirements, and buyer obligations into the agreement—not into an afterthought.
- Choose eligible systems, date ranges, and exclusions.
- Define de-identification and review requirements.
- Specify permitted uses and onward-sharing restrictions.
- Agree on retention, deletion, and payment terms.
CONTEXT IN. IDENTIFIERS OUT.↗
ILLUSTRATIVE SOURCE RECORD
Alex Chen resolved the renewal blocker for Acme Co. after the support handoff.
ILLUSTRATIVE PREPARED RECORD
PERSON_01 resolved the renewal blocker for COMPANY_02 after the support handoff.
Ownership stays with you.
A license grants defined usage rights. It doesn’t have to mean selling ownership of your underlying data.
No blanket permissions.
Buyer access, exclusivity, and future uses belong in the terms you review and approve.
Fit before a forecast.
Value depends on buyer demand, usable history, quality, and rights—not a universal price per record.
A little clarity
goes a long way.
Data licensing is a commercial decision. Here’s what to consider before taking the next step.
What kinds of businesses are a fit?
Businesses with useful operational records and the authority to license them are a starting point. Rich workflows, well-organized history, and clear outcomes may be relevant. Fit is assessed against buyer needs; not every dataset will qualify.
How much could our data be worth?
There is no reliable one-size-fits-all estimate. Pricing depends on uniqueness, completeness, volume, licensing rights, preparation work, exclusivity, and demand. Any valuation should follow a dataset assessment and a specific commercial proposal. Revenue is not guaranteed.
Do we need to connect all our tools?
No unrestricted access should be necessary to begin the conversation. Start with a description of your systems and available records. If there is a fit, the scope and transfer method can be agreed before any data moves.
What about personal or confidential information?
Sensitive fields, third-party obligations, consent, and applicable laws must be reviewed before transfer. Some records may need to be excluded entirely. De-identification reduces privacy risk but does not eliminate it. Your legal and security teams should review the proposed arrangement.
Can we license the same data more than once?
Potentially, if your ownership rights and agreements permit non-exclusive licensing. Buyer demand and restrictions will vary. Repeat revenue should be treated as an opportunity, not a promise.
What will AI labs be allowed to do with it?
The signed license should specify the allowed purposes, such as model training or evaluation, and any restrictions on publication, redistribution, retention, or onward access. Those rights should be clear before delivery.
Let’s see what’s possible
You’ve built a business.
Let’s uncover what
else it can grow.
Start with the basics. Tell us about your business and data footprint, then book a conversation about the opportunity.
No data uploads. No system credentials.
Just a starting point for a better conversation.