Constantine LLC is sourcing this opportunity on behalf of a third-party organization who is seeking qualified agencies and organizations that can provide access to high-quality, real-world operational data, workflows, domain expertise, and associated documentation suitable for use in advanced artificial intelligence training, evaluation, and reinforcement-learning environments.
The objective of this RFP is to identify and onboard five qualified agency partners within the next 60 days.
The opportunity is intended for organizations that possess meaningful, specialized, and legitimately sourced data arising from real-world professional activity. Relevant data may include operational workflows, procedures, standard operating procedures (SOPs), decision-making processes, structured or unstructured records, domain-specific documentation, examples of expert work, quality-control processes, edge cases, and other materials that can help AI systems learn how complex work is actually performed.
The initiative is designed around the broader objective of transforming human expertise and real-world workflows into measurable improvements in AI capability.
Their role is specifically to provide, license, facilitate access to, or otherwise participate in the authorized transfer and/or collection of relevant data and expertise.
Modern AI systems require more than large quantities of generic information. They increasingly require access to real-world examples of how skilled professionals make decisions, execute workflows, handle exceptions, assess quality, and respond to unusual situations.
This RFP seeks organizations whose data can contribute to that objective. The intended data may ultimately support:
The central objective is not simply to acquire a static dataset. Where appropriate, the engagement may support a broader data pipeline in which real human expertise establishes what good performance looks like, automated systems expand that expertise into additional scenarios, and quality-control processes identify the cases where expert review creates the greatest value.
This creates a continuous improvement cycle in which real-world expertise can contribute to increasingly capable AI systems.
The program uses a human-in-the-loop approach to AI data development.
At the foundation are real-world environments and workflows in which domain experts demonstrate or establish appropriate standards of performance.
These environments can capture:
Once these standards are established, technology can help expand the resulting expertise into additional environments, scenarios, rubrics, variations, and edge cases.
Automated quality-control processes can then evaluate outputs, identify important failures, and route selected cases back for human review. The resulting feedback loop can produce increasingly valuable training and evaluation signals.
The broader objective is therefore to move beyond simply producing data toward creating repeatable and measurable units of intelligence improvement.
We are particularly interested in established agencies and organizations that possess substantial access to specialized professional information or operational workflows.
Applicant organizations should have a minimum of 15 employees. Potential partners may include, but are not limited to:
The relevant consideration is not the agency’s marketing reach or ability to acquire customers.
The relevant consideration is whether the organization has access to valuable, legitimate, sufficiently detailed real-world data or human expertise that can contribute to AI training, evaluation, or real-world reinforcement-learning environments.
The primary requirement is that the relevant data and associated documentation be in English. Organizations should clearly identify the language composition of their proposed data.
Examples of potentially relevant data include:
Operational Workflows
Professional Work Product
Expert Decision-Making
Data illustrating:
Domain-Specific Data
Specialized information associated with industries such as:
Edge Cases and Exceptions
Particularly valuable data may include examples of:
These examples can be particularly useful because they expose the circumstances in which automated systems are most likely to fail.
All proposed data must be provided on a lawful and authorized basis. Organizations responding to this RFP must be able to explain:
Data involving individuals, customers, employees, patients, consumers, or other identifiable persons must be appropriately handled in accordance with applicable privacy, contractual, and regulatory requirements.
Partners should not submit data merely because they can technically access it. They must have the appropriate legal and contractual authority to provide it for the contemplated use.
Privacy and security are fundamental requirements of the program.
Depending on the proposed dataset, selected partners may be required to support:
The specific controls required will depend on the nature of the proposed data.
Partners should disclose known privacy, confidentiality, security, or regulatory considerations in their proposal rather than waiting until the final contracting stage.
High volume alone is not sufficient.
Proposals will be assessed in part on the quality, usefulness, uniqueness, relevance, and realism of the proposed data. Partners should provide information regarding:
Where applicable, partners should explain how the organization currently validates the accuracy of its data.
A particularly important consideration is whether the proposed material reflects actual work performed in real operating environments rather than purely synthetic or theoretical examples.
Organizations should explain:
Data that captures the complexity of actual professional work may be particularly valuable for developing AI systems that must operate reliably in real-world environments.
The exact structure of each partnership will depend on the dataset and the rights available. Potential engagement structures may include:
One-Time Data License
A defined dataset is provided under an agreed commercial license for an agreed period and permitted use.
Recurring Data Partnership
A partner provides periodic updates or additional data according to an agreed delivery schedule.
Structured Data Access
The partner provides controlled access to a defined data environment or repository.
Workflow-Based Engagement
The partner provides access to real-world workflows, examples, documentation, or expert-reviewed materials that can be incorporated into structured AI environments.
Hybrid Model
A combination of historical data, ongoing data delivery, documentation, expert input, and quality review. The final structure will be determined during commercial and technical diligence.
Step 1 — Submit a Proposal. Interested organizations begin by submitting a proposal in response to this RFP (see Section 16 for response requirements).
Step 2 — Initial Approval. If a proposal receives a green signal following initial review, the organization will be directed to the data partnerships team’s designated portal, where they will complete a short information form (approximately a 2-minute task).
This step is required and must be completed before any meeting is scheduled. The process is strict: organizations will not be advanced to a meeting or further evaluation stage until the portal step has been completed.
Selected partners may also be required to interact with multiple systems during the evaluation and onboarding process. Depending on the engagement, organizations may be directed to:
Use of a third-party platform does not change the nature of the engagement.
The partner’s core responsibility remains the provision and authorized delivery of the agreed data and/or associated expertise.
Where a designated portal is used, the responding organization may be instructed to submit datasets, documentation, questionnaires, technical information, or other requested materials directly through that portal.
Partners should therefore be comfortable working through external systems when required.
Selected organizations may be responsible for:
Partners are not being engaged to:
The engagement is fundamentally a data and expertise partnership.
The anticipated budget is: $100,000–$3,000,000 per selected agency
The final commercial value may vary substantially depending on factors including:
The stated range is an indicative partnership budget, not a guaranteed payment.
Organizations should provide their proposed commercial structure and explain the basis for their pricing. Proposals should clearly distinguish:
The objective is to identify and onboard: 5 qualified agencies within 60 days
The program may evaluate a substantially larger pool of organizations in order to identify the required number of qualified partners. There is no requirement that all five partnerships use identical commercial structures or identical data formats.
The program may select organizations across different industries and data categories where doing so increases the diversity and usefulness of the resulting data ecosystem.
The program is open to qualified organizations internationally.
However, U.S.-based agencies may receive priority consideration, particularly where their data provides substantial coverage of U.S. professional workflows, operations, or markets.
Geographic preference does not replace the core qualification requirements.
Organizations outside the United States may still be considered where their data provides strong relevance, quality, uniqueness, and authorized access.
Interested organizations should provide a concise but sufficiently detailed proposal covering the following areas.
Organization Profile
Data Overview
Describe:
Data Rights
Explain:
AI Use Potential
Explain how the data could support:
Data Quality
Describe existing:
Commercial Proposal
Provide:
Delivery
Explain:
Sample Availability
Where legally permitted, provide or describe a representative sample sufficient to evaluate the data’s structure and potential usefulness.
The anticipated process is:
Stage 1 — Initial Review
Submission is reviewed for basic relevance, data ownership, domain fit, and commercial feasibility.
Stage 2 — Data & Organization Assessment
The proposed dataset and organization are evaluated in greater detail.
Stage 3 — Technical / Data Review
The parties may review: Sample data, Schema, Metadata, Documentation, Data provenance, Quality controls, Delivery mechanisms.
Stage 4 — Legal & Privacy Review
The proposed use, licensing rights, privacy requirements, confidentiality provisions, and other applicable considerations are reviewed.
Stage 5 — Commercial Discussion
Pricing, scope, licensing, delivery, duration, and other commercial terms are negotiated.
Stage 6 — Onboarding
Selected partners complete required contracting and operational setup.
Stage 7 — Data Delivery / Partnership Launch
The agreed dataset or workflow materials are delivered through the designated mechanism.
The following factors may be considered during evaluation:
No single factor necessarily determines selection.
Organizations should not assume that more data automatically represents a stronger proposal. For AI training and evaluation, the value of data may depend heavily on whether it captures:
Accordingly, proposals should focus on what makes the organization’s data informative and difficult to reproduce, rather than simply reporting a large record count.
Are you asking agencies to find clients or generate leads?
No. This is not an affiliate, referral, lead-generation, or sales program. The objective is to establish partnerships with organizations that possess relevant real-world data, workflows, documentation, or expertise.
Do agencies need to recruit their customers into the program?
No. Agencies are not being asked to recruit customers or transfer unrelated customer relationships. Any third-party data included in a proposed dataset must be provided only where the agency has the appropriate rights and authorization to do so.
What makes a dataset relevant?
Relevant data generally reflects real-world professional activity, specialized workflows, expert judgment, operational decisions, or domain-specific work. Examples include professional work product, operational records, workflow documentation, decision processes, quality-control materials, and difficult or unusual cases.
Does the data need to be in English?
Yes. English is the primary data-language requirement. Organizations should disclose any material multilingual content.
Does the data have to be in a particular format?
No single format is required. Potential formats may include structured datasets, documents, spreadsheets, databases, APIs, archives, workflow records, or other machine-readable or convertible formats. The proposed format should be clearly described.
Does the organization need to own the data?
The organization must have sufficient legal authority and rights to provide or license the proposed data. Simply having technical access to data is not sufficient.
Can confidential data be considered?
Potentially, subject to appropriate confidentiality, privacy, security, authorization, and contractual requirements. Organizations should identify confidentiality restrictions early in the process.
Will personal information be accepted?
Data containing personal information will be subject to additional review and may require anonymization, de-identification, aggregation, or other controls. Organizations should disclose the presence of personal or sensitive information in their proposal.
Is recurring data preferred?
Recurring data can be valuable, but one-time historical datasets may also be considered. The commercial structure will depend on the characteristics and potential use of the proposed data.
What is the expected budget?
The indicative budget is $100,000–$3,000,000 per selected agency, subject to data quality, scope, rights, licensing terms, delivery requirements, and other commercial factors.
How many agencies are being sought?
The current objective is to onboard 5 qualified agencies within 60 days.
Are U.S. organizations required?
No. The program is international, although U.S.-based agencies may receive priority consideration where their data aligns strongly with program requirements.
Will there be meetings?
Potentially. Selected organizations may participate in discovery, technical, legal, privacy, or commercial discussions. Meetings may take place through Zoom or another designated conferencing platform.
Will partners need to use external websites or platforms?
Potentially, yes. Depending on the engagement, organizations may be directed to a designated portal, website, secure data environment, document-management platform, electronic-signature system, Zoom, or another third-party platform.
Will data be submitted through an agency portal?
Potentially. Selected organizations may be instructed to submit samples, questionnaires, documentation, datasets, or other materials directly through a designated partner portal or secure submission environment.
Does responding to this RFP guarantee selection?
No. Submissions will be reviewed against the program’s requirements, and additional diligence may be required before a partnership is established.
Can an organization propose more than one dataset?
Yes. Organizations may propose multiple relevant datasets or data assets, provided each is clearly described and the organization has the appropriate rights to provide them.
Can an organization propose a dataset that requires transformation or cleaning?
Yes. The current condition of the data should be disclosed accurately, including known quality issues, missing fields, formatting limitations, or transformation requirements.
Can a partnership involve expert participation in addition to data?
Potentially. Where relevant, human expertise may contribute to defining workflows, establishing quality criteria, reviewing edge cases, validating outputs, or otherwise improving the usefulness of the resulting AI training or evaluation environment. Any such participation would be separately defined and agreed upon.
What happens after an initial submission?
Qualified organizations may be contacted for additional information, sample review, technical discussions, legal/privacy diligence, commercial negotiations, and onboarding.
Before submitting a proposal, organizations should confirm that they can provide:
Organizations interested in participating should submit their proposal or initial expression of interest to:
A. Amber
Constantine LLC
Email: admin@constantinesolutions.com
Please include “Real-World Data Partnership RFP” in the subject line.
Organizations may initially provide an executive summary if a complete proposal requires additional discussion or confidentiality arrangements.
The purpose of this RFP is to identify organizations capable of contributing high-value, real-world data and human expertise to the development of increasingly capable AI systems.
The program is particularly interested in data that captures the complexity of professional work: the decisions, workflows, exceptions, standards, and expert judgments that are difficult to reproduce through generic or synthetic information alone.
The desired outcome is not merely a larger dataset.
The objective is to establish durable data partnerships that can help transform authentic human expertise and real-world workflows into reliable training signals, evaluation environments, and measurable improvements in AI capability.