AI product workflows
AI products that solve real workflows, not toy demos. We design the interaction model, integrate the right models, and ship products people actually use day to day.
What's included
- LLM-backed assistants and copilots
- Retrieval and embeddings (RAG)
- Multi-step agent or workflow systems
- Human-in-the-loop review and approval flows
- Brand-aware content and creative generation
- Cost / latency / safety guardrails
- Evaluation harnesses and prompt management
When this fits
- You have an AI idea that needs to become a real product, not a notebook demo
- You are adding AI features to an existing SaaS and want it to feel native
- You need a copilot, research workflow or generation tool tuned to your domain
A practical path from rough idea to working product.
Five focused stages. Most projects start with a discovery sprint before committing to a full build.
- 01
Fit call
We check the goal, constraints, timeline, and whether IMME is the right fit.
- 02
Discovery sprint
We turn the idea into scope, user flows, technical plan, risks, and a build estimate.
- 03
Design prototype
We design the key flows first so the product feels real before full development starts.
- 04
Build and integrate
We develop the frontend, backend, database, auth, payments, AI integrations, analytics, or app systems.
- 05
Launch and improve
We ship, test, measure, fix, and improve based on real usage.
Proof we ship this kind of work
Our own products, live and in use. Client work stays private unless the client wants it featured, so ask on a call and we will walk you through similar builds.
Example build concepts
Honest product concepts, not client case studies. Each one shows how a build like this is scoped, what ships, and a realistic timeline.
Turn a manual research process into a guided AI workflow with review, saved context, and exportable briefs.
A content workflow platform with briefs, AI assisted drafts, review queue, brand context, and export tools.
Common questions
- Which AI models do you build with?
- Whichever fits the job and the budget. We compare current models on your real task during discovery, measuring quality, speed and cost, rather than defaulting to one provider.
- How do you stop an AI feature from getting things wrong?
- We design for it. That means retrieval from your own data, evaluation sets that catch regressions, human review where mistakes are costly, and clear limits on what the feature is allowed to do.
Other services
Dashboards, admin portals, subscriptions, auth, payments, analytics, APIs, and internal tools.
Secure portals, booking systems, document flows, reporting dashboards, and operational software.
Cross-platform apps, mobile games, lobbies, profiles, notifications, rewards, and social features.
Marketing pages, waitlists, product storytelling, SEO foundations, analytics, and conversion-focused flows.
UX audits, design refreshes, onboarding rewrites, conversion tuning, performance and SEO improvements for products already live.
Tell us what you want to build.
Send the rough version. We can help shape the scope.
A 20 minute fit call covers the goal, constraints, and whether IMME is the right fit.
Usually replies within one business day.