Operational documentation
SOPs, knowledge bases, internal documentation, CRM data, project histories, and QA processes
Get in touchLettus AI sources and prepares company-owned operational data — workflows, documents, field video, audio, and images — for potential partnerships with frontier AI labs.
Get in touchOperational data captures how businesses actually operate — in documents and systems, and in the video, audio, and images recorded where the work happens. These assets help frontier AI models learn how companies work in practice.
SOPs, knowledge bases, internal documentation, CRM data, project histories, and QA processes
How teams evaluate information and make operational decisions
Human feedback on AI outputs in real business environments to improve model performance
Company-owned material across documents, structured records, and media captured where the work happens. Original material is sourced into a controlled environment; what a partnership licenses is the processed dataset prepared from it.
SOPs, playbooks, tickets, project history
The repeatable steps, handoffs, and exceptions that show how work actually moves through a company.
Docs, slides, sheets, PDFs, email threads
Written material produced in the course of business, carried over with the authorship and timestamps that give it context.
Task capture, walkthroughs, inspections
Recorded in real working environments, where physical steps and judgement calls are visible rather than described after the fact.
Calls, dispatch, shop-floor and field recordings
Spoken work as it happens, including the interruptions, corrections, and background conditions of a live environment.
Photos, scans, diagrams, annotated captures
Visual records of equipment, sites, documents, and conditions, paired with what the company recorded about them.
Corrections, QA judgements, expert annotation
Qualified people assessing outputs and decisions, recorded alongside the work the assessment refers to.
A simple, privacy-first process designed for long-term participation.
Get started
Share basic information about your company and the operational data you may be able to contribute. This takes about 2 minutes.
Share basic information about your company and the operational data you may be able to contribute. This takes about 2 minutes.
Our team reviews your submission to determine whether your company's operational data is a fit for frontier AI training partnerships.
If there's a potential fit, we'll request additional information and schedule a discovery call to discuss your data and privacy requirements.
If approved, we'll finalize the agreement and data requirements and begin the partnership.
These are the everyday tools where workflows, decisions, and institutional context already live.
BigQuery, Snowflake, Databricks
Table schemas and the structured records behind them, rich, interconnected, and built to mirror how the business runs.
Slack, Microsoft Teams, Google Chat
Full conversation histories, threads, participants, and reply structure preserved intact.
Gmail, Outlook, Google Calendar
Email threads and event details, senders, recipients, invites, and the responses that connect them.
Word, Docs, Slides, Excel, Sheets, Drive, SharePoint
File contents plus their metadata, authorship, timestamps, and access permissions.
Jira, Confluence, Asana, Notion, Linear
Tickets, wikis, and project records carried over with their complete history and metadata.
Salesforce, HubSpot, Workday, ServiceNow, SAP, Zendesk
CRM, HR, ERP, and support records from the core systems teams operate in every day.
We partner with established operators, drawing signal from the everyday systems your teams already run on and from media captured where the work happens. We never connect to live systems: material is sourced into a controlled environment, and partnerships license the processed, de-identified datasets prepared from it.
Industries of interest
Every engagement is evaluated individually. Value reflects scope, quality, permitted use, refresh cadence, and active demand for the operational knowledge involved.
$75k+
A clearly scoped dataset from one business function, assessed for relevance, quality, and permitted use.
$250k+
Connected context across several workflows or systems, potentially including agreed recurring updates.
$750k+
Deep, differentiated operating history at enterprise scale, subject to diligence and active demand.