From idea shape to shipped system.
Some teams need a concept sharpened. Some need a roadmap. Some need the first production AI feature. Some need the whole product brought to life. The engagement changes with the problem, but every one runs against the same set of principles. The goal is not to sell a standard agency package; it is to match the right level of strategy, architecture, and implementation to the decision in front of you. If none of these fit, the email is one click away.
Concept Development
Shape the product before the build. Clarify the promise, user, workflow, data advantage, and why AI belongs.
A sharpened concept package — product thesis, target user, core workflow, differentiation, AI role, risks, and next-build recommendation — ready for validation, prototyping, or fundraising conversations.
- — Founders or operators with a strong idea that still needs product shape
- — Teams exploring where AI creates real advantage instead of another demo
- — Companies deciding whether to build, partner, buy, or wait
- — Product thesis and target user definition
- — Workflow sketch and core user promise
- — AI role: what the system should automate, assist, draft, or refuse
- — Differentiation and market-positioning notes
- — Data advantage and feasibility assessment
- — Recommended next step: prototype, strategy sprint, MVP, or no-build
- — The raw idea and why it matters now
- — Any customer, market, or internal context you already have
- — Permission to challenge the premise before turning it into scope
AI Strategy Sprint
A practical AI product plan you can act on before committing build budget.
A written strategy package — product vision, AI concept, technology recommendations, phased roadmap, and a cost-and-risk read — delivered with a live readout and the rationale behind every recommendation.
- — CEOs and founders who know AI matters but don't yet know where it fits in their product
- — Teams about to commit a six-figure build budget who want product judgment before they spend it
- — Boards that need a credible, honest plan to point to instead of hype
- — Discovery sessions with stakeholders, customers (when relevant), and an audit of the current product or codebase
- — A written product and AI vision document — where the product goes and why
- — Specific feature concepts with the user and business case for each
- — Technology and architecture recommendations with rationale, including model choices and integration approach
- — A phased roadmap with sequencing, dependencies, and decision gates
- — Cost, risk, and hire-or-buy analysis grounded in real numbers
- — 60-minute readout to your team or board, plus 30 days of async follow-up
- — A single decision-maker who can act on the recommendations
- — Access to the people closest to the work — engineers, customers, executives
- — Honest answers about budget, timeline, and team constraints
AI Sprint
Ship one production AI feature, end-to-end. Existing product or new build.
A working, production-quality AI feature shipped — into your existing product or as a new build — with code, infra, a 30-minute walkthrough, and the architecture decisions documented.
- — Teams with an existing product that need to decide where AI fits and ship the first feature without disrupting the codebase
- — Companies with a defined feature hypothesis that needs proving in production, not in a deck
- — Founders who want strategy and implementation close together
- — Discovery call and one-page scope document
- — Working AI feature deployed to your staging environment
- — Production-quality code in your repo (TypeScript, Python, or Swift)
- — Architecture diagram and operating notes
- — Live walkthrough and 30 days of async support
- — Repo access and a single technical point of contact
- — Decision authority — one person who can say yes or no
- — Realistic test data (not toy examples)
Product Launch
From validated concept to production MVP. Web, mobile, or both.
A production MVP with auth, payments, an AI feature that matters, and a real user able to log in and complete the core flow.
- — Founders with a validated problem and no engineering team
- — Operators inside larger companies who need to skip the IT queue
- — Anyone who has been 'about to start' for six months
- — Architecture and stack decisions documented and defensible
- — Web (Next.js) and/or native iOS app, deployed and live
- — Auth, payments (Stripe), email, and one AI feature integrated
- — Multi-tenant data model with row-level security if relevant
- — Handoff package: runbook, env setup, deploy process
- — Two weeks of post-launch support included
- — A written one-pager: problem, user, the one thing it must do
- — Weekly 30-minute review with a decision-maker
- — Honest answers when scope gets challenged
Fractional Head of AI Product
AI product leadership embedded with the team and tied to shipped outcomes.
Your AI roadmap, hiring plan, and shipping cadence — shaped by product judgment and daily hands-on technical execution.
- — Series A–B companies with engineering but no AI product leader
- — Boards or CEOs who need to credibly claim 'we have AI product leadership'
- — Teams stuck between 'we built a demo' and 'we shipped to customers'
- — Embedded as AI product and engineering lead on your AI workstreams
- — AI roadmap aligned to revenue and customer outcomes, not hype
- — Hiring scorecards and interview loops for AI roles
- — Two shipped features per quarter as proof, not promises
- — Board-ready monthly briefing on AI program status
- — Clear reporting line — usually CEO or CTO
- — Two days per week of focus time, the rest is async
- — Permission to say no to bad ideas without political cost
Clear thinking, visible progress, accountable delivery.
The shape of the engagement changes; the operating standard doesn’t.
The first week
Every engagement opens with a written one-page scope: the outcome, deliverables, timeline, decision-maker, and what we need from you — signed before work starts. Repo access and a shared channel are set up on day one, and the foundational decision is on the table in writing by the end of week one.
The weekly rhythm
One thirty-minute review per week with the decision-maker; everything else moves async through short written updates — what shipped, what's blocked, what needs a yes or no. Commits flow into your repo and deploys land on a preview URL from day one. No two-week silences followed by a big reveal.
How decisions get made
Scope changes get a written impact note — effort, cost, and what gets cut — before they happen. Disagreements are surfaced early, in writing, with the reasoning; you can override any recommendation knowing exactly what tradeoff you're accepting.
Your repo, your keys
Everything lives in your repo, on your platform, under your accounts. Architecture decisions are documented as short, dated notes committed alongside the code. Production credentials stay with you — every deploy runs through your CI/CD or hosting account.
The handoff
Every engagement ships with a runbook, environment setup, deploy process, and a written list of known issues. Code is yours under a clean assignment from day one, and Sprint and Launch engagements include two weeks of post-launch async support.
The style
Direct — expect pushback on scope, timeline, and the AI feature you're convinced you need. Written — async and traceable, with meetings reserved for decisions that genuinely need them. On time — if something slips, you hear the day we know. And integrated — the people shaping the recommendation are the ones implementing it.
Because engagements vary in scope and your situation is specific. The tier signals the magnitude — small, medium, large, or sustained. The exact number is set after a short scoping exchange where we both know what we're agreeing to. You'll never get an opaque six-figure quote; you'll get a written scope and a fixed price before any contract is signed.
$ is a focused, two-week strategic engagement. $$ is a four-week build sprint. $$$ is a multi-month MVP or recurring leadership engagement. The tiers are anchored to durations and deliverables, not to your budget. If your situation needs a tier we haven't listed, email rob@hideview.com.
No. Every engagement has a defined scope and outcome. The value is product judgment plus execution, not bodies in seats.
Core product and architecture work stays close to delivery. For specialized needs — design polish, mobile distribution, regulated infrastructure — trusted specialists may be brought in with your approval.
Standard mutual NDA up front. All work product is yours under a clean assignment. Client code is never reused in other engagements.
Yes. Below the AI Strategy Sprint ($) tier, you're usually better served by a tool, a template, or a generalist contractor. HideView is best when the scope is meaningful enough to justify product judgment end-to-end.
AI product strategy, concept development, MVPs, vertical SaaS, web and mobile apps, agent systems, voice interfaces, multimodal workflows, AI visibility infrastructure, data products, internal tools, automation, and production hardening.