A prospect came to us last year with a request. They wanted a $200,000 production build. They had a budget approved, a project plan drafted, and a vendor short list. We were on the short list.
We told them no.
Not no to the work. No to the production build. We said we would do a $30,000 Proof of Concept first, against their real data, with a working demo at the end of two weeks. If the POC did not show the math we projected, they would not pay for the production build that followed. If it did, we would scope production with the architecture we had just validated, not the architecture we had guessed at on a sales call.
They said yes. Three months later they were live, fully scoped, and the engagement returned 9.6 times its cost in the first year.
That is not a sales story. That is the case for why every Heed engagement starts with a Proof of Concept.
Why Most AI Projects Skip the POC Step
The honest answer is that POCs are uncomfortable for both sides of the table. The vendor wants to lock in the larger engagement. The buyer wants to feel like progress is being made. A POC delays the larger contract by two to four weeks and forces both parties to confront whether the original assumption was correct.
So the POC gets skipped. The vendor writes a Statement of Work based on a few discovery calls. The buyer signs. Six months in, half the integrations do not work the way they were supposed to, the data is messier than anyone anticipated, and the model needs more guardrails than the budget allows. The project finishes late and over budget, or it gets cancelled.
The fundamental problem is that AI architecture decisions are not safe to make on assumption. You cannot know how a model will perform against your data until you run it against your data. You cannot know how a connector will behave against your production system until you wire it up. The POC is the cheapest way to find out.
What the Heed POC Actually Delivers
A Heed POC is not a slide deck. It is not a wireframe. It is a working system, deployed against a representative slice of your real data, with the actual integrations and the actual reasoning layer running end to end. We aim for a two-week build window with a live demo at the end.
Specifically, the POC includes four deliverables.
Real data corpus. We ingest a representative slice of your actual data. For a structural engineering firm that meant project files, plan sets, and permit history. For a law firm that meant matter records, billing data, and document templates. We do not work on synthetic test data because synthetic data does not show you the messiness of production.
Real connectors. Read-only connectors against your live systems. We are not building a CRM clone in a sandbox. We are connecting to your Salesforce, your SharePoint, your QuickBooks, your case management system. Read-only means we cannot accidentally damage anything in your production environment, but we are pulling the same data the production build will use.
Real agentic workflows on real workflows. Pick the highest-value workflow you have. We build the AI layer for that workflow, end to end. If it is project knowledge search, we build the search. If it is meeting transcript triage, we build the triage. By the end of two weeks, your team can use it.
Real ROI projection. Based on what we built and what we observed, we update the financial model. Hours saved, blended hourly rate, payback period. Sometimes the math gets better than we projected. Sometimes it gets worse. Either way, you get the truth before you sign the production contract.
What the POC Does Not Prove
We need to be honest about this. A two-week POC against a slice of your data does not prove four things.
It does not prove scale. Running against 10,000 records is not the same as running against 10 million. The architecture may need adjustments to handle full production volume. We flag the scaling considerations during the POC review.
It does not prove edge cases. The 5 percent of your workflow that is weird, manual, and judgment-heavy is exactly the part the POC will not stress-test. Production will. The POC tells us where to put guardrails, not where every edge case lives.
It does not prove the full security model. The POC runs in a controlled environment. Production needs full SSO, role-based access control, audit logging, data residency, and the rest of the security stack. We design that during production scoping.
It does not prove operational fit. Will your team actually use it the way it was designed to be used? That answer comes from the first 30 days of production deployment, not from a demo. The POC gets us to the right architecture. Adoption is its own discipline.
Our POC Framework
We run every POC the same way. Day one to three: data ingestion and connector wiring. Day four to seven: core agentic workflow build. Day eight to 10: refinement against your team's feedback. Day 11 to 14: demo prep and ROI model update.
We demo twice. The first demo is internal, with your immediate stakeholders, to catch anything we got wrong about the workflow. The second demo is for the broader leadership team, with the refinements baked in. By the end of demo two, the production scope writes itself.
The Structural Engineering Story
The prospect we mentioned at the top was California's largest hillside structural engineering firm. They had 50-plus employees, multiple regional offices, and they were 85 percent through a Salesforce migration that was not going to solve their actual problem. Their problem was that 25 years of project knowledge was scattered across SharePoint folders, plan sets, photos, permit applications, and budget spreadsheets, and nobody could find anything fast.
Our POC connected to their live Salesforce, SharePoint, and QuickBooks Time. We built a search layer that understood project knowledge the way an engineer would, not the way a database would. The first demo showed it working against three of their active projects. The second demo showed it working across their full active project list. They signed the production scope the next week.
For the full case study, see how we replaced their stalled Salesforce migration.
Why This Matters for You
If you are evaluating AI vendors and one of them is willing to skip the POC step, ask yourself why. The answer is usually that they need the contract more than they need the project to succeed. We need both.
If you have a workflow you want to validate and you are not sure whether AI is the right answer, the POC is how you find out without betting six figures on the question. Most of the time the math works. When it does not, the POC saves you the production budget you would otherwise have spent on the wrong architecture.
Either outcome is better than guessing.