Frame the outcome
We turn the work a team needs done into a written outcome, authority boundary, set of constraints, and definition of done. That gives the customer and the builders one testable target before implementation begins.
About Intent Solutions
Intent Solutions is an applied AI engineering company that turns AI capability into reliable, measurable production work for operators, technical founders, and delivery teams.
We connect engineering, evaluations, demos, teaching, open-source tools, and products around the same work. Customer operating knowledge and independence are part of the delivery.
The company in 30 seconds
How the engineering, evaluation, demos, teaching, and open-source work connect. No narration; the film is on-screen text and music.
Read the film’s on-screen text
- Intent Solutions. Applied AI engineering.
- Build useful technology.
- Define done.
- Test the claim, in Labs and Evals: outcome, constraints, evidence.
- Show the work, in Demos.
- Share the method, in Learn.
- Build in public, with OMA desktop tools.
- Make it reusable, through Tons of Skills agent skills and plugins.
- Services. Products. Open source.
- One connected company.
- Built. Tested. Shared.
- Request an outcome at intentsolutions.io.
The visuals illustrate connected work. They are not customer results or recordings of a product running. Music: “Hazy After Hours” by Alejandro Magaña (A. M.), via Mixkit.
What Intent Solutions does
We carry one outcome through four operating stages, then expose useful evidence and tools through the public network.
Build the operating system around the AI
We design the context, tools, handoffs, human approvals, and failure paths around the model. The result is a production system that fits the customer’s work instead of a disconnected demonstration.
Prove the claim
We evaluate the behavior against the agreed test and keep failed results visible with the passes. Customers get evidence they can inspect, date, and reproduce before treating the system as done.
Operate and transfer capability
We agree on ownership, monitoring, rollback, documentation, access, and knowledge transfer before handoff. The designated customer team demonstrates the agreed operating and change tasks, with any continuing support defined in scope.
Publish the useful parts
Engineering work informs Labs and Evals, working Demos, practice through Learn, implementation notes at Start AI Tools, and reusable tools through OMA, GitHub, and Tons of Skills. Repeated needs can become products, and the resulting knowledge improves the next deployment; publication and reuse depend on permission and licensing.
What makes Intent Solutions different
The standard stays fixed even when the model, vendor, runtime, or delivery channel changes.
Done is defined before the build
Every engagement starts with the outcome, accountable party, authority, constraints, evidence, and stopping conditions. That definition becomes the acceptance test instead of leaving success to a presentation at the end.
Failed evidence stays visible
A failed evaluation is part of the record, not a result to hide. This makes the limits of a system inspectable and gives the next change a concrete regression target.
Operations are part of delivery
The work includes monitoring, cost controls, rollback, and a named response when the system is wrong. A system is not complete merely because it produced the right output once.
Customer capability is part of done
We build with the people who will own the system and agree on knowledge transfer and an exit path from the start. The handoff covers how to run, evaluate, investigate, and change the agreed workflow, with third-party dependencies and rights made explicit.
The work can be inspected before the pitch
The public network includes working demos, evaluation records, definitions, field notes, and source-linked tools. Each artifact states what it demonstrates and avoids turning a public example into a promise about a customer result.
Who uses Intent Solutions
The practice is designed for teams with a concrete operating problem and a real standard for deciding whether the work succeeded.
- Operators who need an AI system with a written test, a responsible owner, and a rollback path.
- Technical founders moving an AI workflow from a working prototype into a production operating loop.
- Teams that need human control, inspectable evidence, and a clear response when an AI component fails.
- Practitioners who want to learn the Intent method and show their work through the separate Learn practice.
The team behind Intent Solutions
The people responsible for engineering, operations, instruction, project delivery, and legal guidance.
Jeremy Longshore
Founder & CEO
Heather C. Johnson, JD
Legal Counsel
Pablo Perez
Co-Founder & Project Manager
Max Sheahan
Lead Instructor
Tim Neunzig
Head of German Operations
Jeremy Longshore, founder
Jeremy Longshore founded Intent Solutions and leads its work from Gulf Shores, Alabama after an operations career. His public work centers on production AI systems, the Claude Code ecosystem, and the discipline required to move from a demo to a system someone can own.
How the company began
Intent Solutions grew from building AI systems and open developer tools, then documenting what held up under real operating pressure. The company made that method explicit: define done, test the claim, keep the failures, and assign responsibility for what runs.
The operating team
Engineers, operators, instructors, and project leaders contribute to system delivery, evaluation, teaching, and ongoing operation. The team works under one Intent Solutions standard across Learn, Labs, Demos, and the other network properties while models and providers remain replaceable components.
Public profiles
Follow Jeremy’s engineering work on GitHub and his professional profile on LinkedIn. The company’s public systems and evidence are linked throughout this page and in the site map.
How Intent Solutions works
The engagement follows the same sequence shown in the public method: Frame, Build, Prove, Operate.
Start with the outcome
Use the outcome request or email support@intentsolutions.io with what must change and how you would recognize a useful result. Every request receives a fit review, but the site does not publish a response-time guarantee.
Write the acceptance test
The customer and Intent Solutions define the outcome, constraints, authority, evidence, and stopping conditions together. That written frame controls the build and gives both sides the same definition of done.
Work with the accountable team
Customers work with the founder-led delivery team responsible for the system, evidence, and operating handoff. The assigned people and communication cadence are set during framing because they depend on the scope and the systems involved.
Set the schedule from the work
Intent Solutions does not publish a generic turnaround promise. Delivery milestones are established after the outcome, dependencies, approval boundaries, and acceptance test are known.
Prove and operate
The system is evaluated against the agreed claim, with failures retained as evidence and regression targets. Delivery includes operating ownership, observability, rollback, cost controls, and a demonstrated handoff so the customer can maintain and improve the agreed workflow.
Key facts
Short, extractable facts about the company and its relationship to the wider Intent Solutions network.
| Company Name | Intent Solutions |
|---|---|
| Type | Applied AI engineering company |
| Founded | 2025 |
| Founder | Jeremy Longshore |
| Headquarters | Gulf Shores, Alabama, United States |
| Website | https://intentsolutions.io/ |
| Core Offering | Design, evaluation, delivery, and operation of production AI systems around defined business outcomes |
| Pricing | Scoped per engagement; not published on this site |
| Contract Terms | Agreed per engagement |
| Services | Outcome framing; system design and build; evaluation; operational handoff and support |
| Communication | Outcome request form; support@intentsolutions.io |
| Projects Delivered | Projects and Demos publish examples; a total count is not published |
| Social | GitHub and LinkedIn |
| Network | Intent Labs, Evals, Demos, Learn, Omarchy, Tons of Skills, Start AI Tools, DiagnosticPro, and Hustle |
Frequently asked questions
Answers about fit, onboarding, commercial terms, the public evidence, and the wider network.
What is Intent Solutions, exactly?
Intent Solutions is an applied AI engineering company focused on the work between AI capability and reliable production use. We engineer workflows, integrations, evaluations, and human oversight, then transfer the knowledge needed to operate and evolve the agreed system.
Who is Intent Solutions for?
It is for operators, technical founders, and teams that need an AI system they can test, own, and run. It is a poor fit for someone seeking an untested prototype, a generic prompt pack, or a result with no accountable operator.
How is Intent Solutions different from other AI implementation providers?
Done is defined before the build: the outcome, constraints, authority, evidence, and stopping conditions become the acceptance test. Failed evaluations stay in the record. Monitoring, cost controls, and rollback are part of delivery, and the handoff covers how the customer team runs and changes the agreed workflow.
How does onboarding work?
Start by describing what must change, where the system must run, and what evidence would make the result trustworthy. We review the fit, then write the outcome, constraints, acceptance test, and operating responsibilities before the build begins.
What does Intent Solutions charge, and are contracts required?
Current pricing and contract terms are not published on this site and must be confirmed for the specific engagement. The request process starts with the outcome so scope and commercial terms can be tied to the actual work.
How does this relate to the other Intent Solutions sites?
The sites are connected parts of one applied AI engineering company. Engineering produces evidence, demos, and lessons; permitted reusable components reach GitHub, OMA, and Tons of Skills, while Learn and Start AI Tools transfer knowledge and repeated needs inform products.
Where can I inspect the evidence, source, or demos?
Start with Intent Labs for dated results, Demos for working systems, Projects for public work, and GitHub for source-linked artifacts. Those materials demonstrate the method and specific behavior; they do not promise that a different system will produce the same result.
Have a defined outcome or an operating problem that needs one?
Request an outcome