• Who is your ideal customer right now (not “in the future”)?

Ideal paying client (right now): A government workforce stakeholder that has (1) a mandate to place veterans into good jobs, (2) budget authority for workforce tools, and (3) pressure to show measurable outcomes (placements, time-to-employment, retention).
Ideal “customer” organizations (right now): Utilities and manufacturing employers with high-volume skilled trades/technician hiring and a clear need to convert non-traditional experience into validated job readiness.
Ideal end users (right now): Transitioning service members and veterans within 12–18 months of separation (plus recently separated vets) who need their skills recognized without résumé translation.

• How did you choose this segment?

Government is the payer because they’re accountable for transitions and workforce outcomes and can fund scalable systems across regions/programs.

• What are their top 2–3 pain points?

1. Slow/inefficient placement pipelines and uneven outcomes across programs.
2. Hard-to-prove ROI (limited visibility into “skills gained” vs “job obtained”).
3. Fragmented ecosystem (training providers, employers, case managers, tools that don’t talk).

• How do they currently solve the problem today?

Government: contractors, training grants, job boards, case management, program reporting, and legacy assessments — often disconnected and slow.

• What surprised you or changed your assumptions?

1. The buyer is the government, but adoption hinges on employers. If utilities/manufacturing managers don’t trust the signal, placements stall.
2. “Translation” isn’t enough — proof is the unlock. Crosswalks help labeling; simulations + cognitive validation create confidence.
3. Speed matters as much as accuracy. Governments want outcomes; employers want fill rates; vets want momentum.
4. Different stakeholders want different receipts: government = metrics/compliance; employers = readiness + safety; vets = dignity + clarity.

• How do customers describe the value of your product in their own words?

Government: “We need a tool that moves people into jobs faster and gives us measurable outcomes we can defend.”

• What is the #1 feature or benefit they care about?

A trusted, job-relevant “skills proof” signal that produces role-fit evidence and makes military experience immediately actionable for hiring.

• What part of the value would they miss most if you disappeared tomorrow?

Government: a scalable way to convert funding into verified employability + placements, with defensible reporting.

• Is this a must-have or just a “nice-to-have”? How do you know?

As it’s funded from core workforce/transition budgets (not pilots-only), it’s a must-have because the buyer is treating our platform as mission-critical infrastructure, not an experiment. If this tool disappeared, they'll miss a goal they’re graded on.

• One signal metric that best represents whether people truly need your solution

Revenue: +$28K in revenue from the DOL for +8 employers onboarded this week; secured $120K+ per quarter for the next 3 years

• Where traction is strongest

Government stakeholders who are accountable for placement + retention metrics. We frame the platform as throughput + accountability infrastructure

• Where the product is failing

Making the platform suitable for all army departments

• What you will iterate next week

Product iteration

• How did you determine your initial pricing?

Benchmarked against workforce SaaS and assessment platforms (per-seat / per-candidate).
Modeled “cost per successful placement” vs. what government and employers already pay (recruiters, training, churn).
Backed into a price that is neutral-to-cheaper than current spend, while supporting our margins.

• What feedback have customers given you about pricing?

Government: “This is reasonable if it’s tied to clear outcomes (placements, completions, retention).”
Employers: Price is acceptable if it replaces some recruiter/assessment spend and doesn’t feel like an extra line item.
General: Less pushback on total price, more on how it’s structured (per seat vs. per hire vs. per cohort).

• How sensitive are they to price changes?

Moderately sensitive on unit price, highly sensitive on budget category.
If it fits into existing workforce/recruiting budgets and replaces something, there’s flexibility.
If it feels “additive” or comes from innovation dollars only, sensitivity is high.

• What is your next pricing experiment (e.g., free trial → paid, usage tiers, value-based pricing)?

[current] Test a “program / placement” model with government: platform fee + per validated hire.
Segment government buyers into three motion types: fast-adopters (regional workforce offices), credibility buyers (DoD pilots), and institutional renewers (DOL multi-year program) — then sequence resource allocation accordingly.

For employers, test a role- or site-based subscription (all candidates for X roles or locations included), instead of per-candidate fees.
Codify a repeatable employer-validation protocol — 30-day trust-building process with simulation demos, supervisor calibration, and post-placement feedback — so employer adoption becomes scalable rather than relational. Prioritize employer demand signals — track placements per employer, supervisor satisfaction, and time-to-first-hire.

• How does your pricing reflect the real value delivered?

Anchored to outcomes they already track: time-to-fill, cost-per-hire, and retention.
Designed so that, when fully used, our cost per successful hire is lower than what they pay today for mis-hires, overtime, and recruiting — and so we only win when they do.

Revenue Model Summary
Our biggest business-model risk is relying on large, slow government contracts where the payer is separate from daily users. To de-risk this, we’re testing tightly scoped, outcome-priced programs with a government partner and a small set of employers, proving unit economics and creating a repeatable playbook for multi-year deals. Early willingness to pay is strongest from veteran/workforce programs and utilities/manufacturers hiring for critical roles, evidenced by funded pilots, data-sharing, and movement into budget/legal review rather than just verbal enthusiasm. If we suddenly raised prices 2–3x, we’d expect government partners to push for narrow pilots and strict guarantees, and employers to shrink scope to single sites or roles—visible through lower win rates and more deals stalling at procurement/finance.

Our decision to keep or change the current pricing model will be driven by Net Revenue Retention plus usage; if usage is strong but NRR is flat, that’s our signal to move toward usage- or value-based pricing so revenue tracks the value we create. Expansion revenue comes in two waves: first, within government contracts (more roles, sites, and programs per agency), and second, through a future B2B model where employers who participate in government-funded programs and see results convert into direct paying clients (site- or role-based subscriptions). This current government-led model is intentionally designed to bring employers into the system early, generate proof of impact for them, and then unlock that B2B expansion path.

Revenue Model Summary
Our initial revenue model is government-led, employer-validated, and B2B-enabled. We generate revenue through government-funded veteran-to-critical-industry programs, where agencies pay platform and/or per-placement fees to validate skills and drive measurable employment outcomes. Within those programs, we work with utilities and manufacturers that supply real roles and sites, creating the data and trust needed to later convert them into direct B2B customers (site-, role-, or program-based subscriptions). Over time, revenue expands by adding more roles, sites, and cohorts per government partner and by upselling employers who want to use the platform beyond the initial program. Pricing is anchored to outcomes they already track (time-to-fill, cost-per-hire, retention), so that our cost per successful hire is lower than their current spend on mis-hires, overtime, and traditional recruiting. As we validate this model, we’ll move toward value- or usage-based pricing where revenue scales with the volume of validated candidates and hires we enable.

The message that consistently converts is: “We replace résumés with real-world, AI-powered skill proof, so you can place veterans into critical roles faster and with less risk—using budgets you already have.” We know it works because it reliably moves conversations from interest to funded pilots, data access, and concrete role/site commitments, not just positive feedback. Our true buyer is the government program owner or workforce decision-maker controlling transition/workforce budgets, while our true users are veterans, case managers, and hiring managers in utilities/manufacturing—so our GTM motion pairs top-down “outcomes and compliance” messaging with bottom-up “ease, fairness, and speed” for practitioners. Customers today rely on résumés, recruiters, staffing agencies, MOS crosswalks, and generic assessments, and we position ourselves clearly as skills-first AI/XR infrastructure that delivers objective proof of readiness, not just better filtering or another job board. Parts of our GTM—like the program structure, core pitch, and pilot-to-expansion playbook—are already repeatable, while enterprise/gov selling, relationship-building, and some reporting/analytics are still founder-dependent and partially manual, which we’ll progressively systematize.

Our most useful recent GTM experiment was leading with a tightly scoped, role-specific pilot proposal (one employer, one or two roles, clear outcomes) instead of a broad “platform” pitch; it dramatically shortened the path from interest to concrete scoping and changed our decision to always anchor first conversations around a specific role + site. The primary metric we use to decide whether a GTM channel is worth doubling down on is “qualified opportunities created per month” that progress to budget/legal review within a defined time window, not just meetings or demos. If we 10×’d our customer base tomorrow, the first things to break would be founder-led sales and bespoke onboarding, so we’re designing around that by standardizing our program templates, onboarding playbooks, and reporting bundles that account teams can run without founder involvement. Our next GTM experiment is to systematically pair government outreach with pre-identified employer champions in critical industries, testing the hypothesis that joint value propositions (agency + employers + veterans) accelerate decisions compared to agency-only conversations. We’ll track whether this “triangulated” approach increases the conversion rate from initial discussion to funded pilot and reduces time-to-signature.