Product & PoC Development
Fast-track your AI ideas into tested prototypes and market-ready MVPs with full-stack ownership.
An honest read on the work
No marketing voice. A direct explanation of what the engagement actually covers and what it does not.
Product and PoC Development is the full-stack build of new AI-backed products from idea to a working system in front of real users. We take ownership of the entire surface — product thinking, UX, frontend, backend, model integration, deployment, and analytics — so a founder or product team can validate an idea on a real timeline without assembling a team first. The engagement compresses what would normally take six months and three hires into a single quarter with a single partner.
This service fits when speed matters: a founder needs a working demo for the next fundraising conversation, a product team needs to validate a new feature before committing it to the roadmap, or a company is testing an entirely new line of business and wants a real artifact in users hands before scaling investment. We are explicit about the difference between a PoC, an MVP, and a production system, and we scope to whichever you actually need rather than over-engineering or under-delivering.
The SoftUs difference is product judgment paired with engineering execution. We will push back on scope that does not contribute to the validation question, suggest the cheapest test that produces the answer, and design the system so the parts that survive into V1 are not throwaway. Our engineers are full-stack — they ship the React frontend, the FastAPI backend, the model integration, the CI pipeline, and the deployment — so there is no handoff drag between disciplines.
We build to a working product, not a Figma file. Every Friday you see a deployed build with the actual user flow, not screenshots. We run user interviews where useful. We instrument the product from day one so the validation is measured, not guessed. You leave with a working product, the analytics to know whether it is working, and a clean codebase your future team can extend without rewriting.
Four situations this service fits
If you recognize yourself in one of these, the engagement will move quickly. If not, we will tell you in week one.
Founder racing to a fundraise
You need a working demo with real AI behavior in eight weeks for a pitch. We compress the build into a single sprint with weekly demos and a deployed product the lead investor can actually click through.
Product team validating a new AI bet
You want to test whether a new AI-powered feature moves a metric before committing engineering capacity. We build it as a standalone PoC, integrate it with your real data, and instrument the validation.
Company entering a new product line
You are launching adjacent to your core product and need a separate team and stack to move fast without blocking the main roadmap. We run as an extension of your team with our own delivery cadence.
Corporate innovation team running a pilot
Your innovation group needs a real pilot to test inside the business — not a slide deck. We deliver a deployed pilot integrated with your real systems, governed by your security review.
Five phases, end to end
The same shape every engagement runs in. Scoped weekly, demoed weekly, with a written deliverable at the end of every phase.
- Phase 01
Discovery & Scoping
1 weekWe define the validation question, agree on the minimum feature set that answers it, sketch the user flow, and lock the timeline. Anything outside the validation question gets cut from scope before we start.
- Validation question and success metric
- Minimum feature set list
- User flow and wireframes
- Timeline and milestone plan
- Phase 02
Design & Architecture
1 weekWe produce the visual design at fidelity, design the data model, choose the model approach for any AI components, and set up the project — repo, CI/CD, deployment target, analytics — before any feature code is written.
- High-fidelity design
- Data model and API contracts
- Repo, CI/CD, and environments
- Analytics instrumentation plan
- Phase 03
Build & Iterate
3 to 4 weeksWe build in weekly increments — full slices through frontend, backend, and model so something is always usable. Every Friday a new build is deployed for review and feedback. Scope is renegotiated only against the validation question.
- Weekly deployed build
- Working end-to-end user flow
- Integrated AI components
- Demo-ready environment
- Phase 04
Validate & Harden
1 weekWe run validation — internal users, design partners, or live traffic depending on the case — instrument the behavior, and produce a written analysis of what the validation actually showed. We tighten the product based on the result.
- Validation run and analytics
- Written validation findings
- Prioritized fix-list
- Security and performance pass
- Phase 05
Deploy & Handoff
1 weekWe deploy to a production environment, transfer ownership of the codebase, repo, and infra to your team or accounts, and run a handoff session. Optional: continue building toward V1 under a follow-on SOW.
- Production deployment
- Codebase and infra transfer
- Handoff session and documentation
- Recommended V1 roadmap
Tangible artifacts, not slide decks
At handoff, you receive a working system plus the documentation, dashboards, and runbooks needed to operate it without us.
The full AI/ML stack, end to end
From data ingestion to model training to vector retrieval to evaluation, we work across the tools production AI teams actually rely on. Reliable, well understood, and easy to hand off.
Languages
Frontend & Full-stack
Backend & AI
Cloud & Infra
Data & Services
Analytics & Observability
Three ways to work with us
Pick the shape that matches your stage. We will tell you honestly if a different model would serve you better.
Fast PoC
A four-to-six week sprint that takes one idea from sketch to deployed product with a real user flow and instrumented validation.
Founders prepping a fundraise or product teams testing a single high-stakes bet.
MVP Build
An eight-to-twelve week build of a market-ready MVP — production infra, real users, billing if needed, and a roadmap for V1.
Founders post-validation who need a real product in users hands before scaling the team.
Embedded Pod
A SoftUs product pod working as an extension of your team for a quarter, running its own delivery cadence on a new product line.
Companies launching adjacent products without disrupting the core roadmap.
What you will gain
Concrete outcomes from our engagement — measurable impact you can track from day one.
Faster investor buy-in with working demos
Early product-market fit validation
Clear roadmap for full-scale product launch
Who we build for
We work across industries where data, AI, and automation unlock real competitive advantage.
SaaS
New feature validation
Fintech
Quick MVPs for funding pitches
HealthTech
Prototype testing with compliance
EdTech
Pilot programs for adaptive learning
Case studies
Examples of how we deliver under real constraints — timelines, data quality, and production requirements.
Smart Meeting Notes Generator
Teams wasted time manually taking notes and creating follow-up tasks from meetings, leading to inconsistent action items.
Built an AI tool that records, transcribes, summarizes meetings, and auto-generates action items with multi-speaker separation and CRM sync.
AI Recruitment Screening Platform
HR teams spent weeks manually screening hundreds of resumes, leading to slow time-to-hire and potential bias in selection.
Deployed an AI platform that semantically scores and ranks candidates against job descriptions, with integrated bias-check modules for fair hiring.
The honest answers
Direct responses to what you would ask on a first scoping call. If your question is not here, send it on the contact form and we will answer in writing within a working day.
How long does a typical engagement take?
A focused PoC runs four to six weeks. An MVP build is eight to twelve weeks. Quarterly embedded pod engagements run on a thirteen-week cadence with a roadmap review every six weeks.
Who owns the code and IP?
You do. Code lives in your GitHub or GitLab organization from day one, infra runs on your cloud accounts when possible, and we assign IP at the contract level. You can take the project in-house at any milestone.
Do you sign NDAs and DPAs?
Yes to both. NDAs sign before discovery. DPAs sign before any data flows. For sensitive data we will run the build inside your environment from the start.
Can you work with our brand and design system?
Yes. We adapt to existing brand systems and component libraries. If you do not have one, we design at fidelity for the PoC and produce something we can extend into a system if the project graduates.
What happens after the PoC — do you keep building?
Up to you. Many clients continue into an MVP build under a follow-on SOW. Others take the codebase in-house. A few keep us on a part-time basis for the next milestone. We make the handoff clean either way.
How do you price?
PoCs and MVPs are flat-fee with milestone payments. Embedded pods are billed monthly per seat. We share the full quote before signing and the scope is locked against the validation question we agreed in week one.
What if the validation says no?
That is a successful PoC. The whole point is to learn fast and cheap. We will deliver an honest write-up of what the data showed and recommend whether to pivot, kill the bet, or run a tighter follow-up.
Can you start from a vague problem?
Yes. Week one is for sharpening the validation question and cutting scope. Most founders come in with three features and leave week one with one — the one that actually tests the thing.
Adjacent work we do
Engagements that often run alongside this one.
Bring this work in-house, fast
A thirty-minute scope call gets you a written plan and a fixed quote. No slide decks, no follow-up cycle.
Have an AI idea, messy workflow, or product vision? Let's make it buildable.
Bring the problem. We'll help shape the product, define the architecture, and show the fastest path to a serious first version.
A practical first roadmap in the discovery call
Architecture, timeline, and delivery options in plain English
Security, scalability, and reliability discussed upfront
Model registry
softus-rag-v4.2
187ms
Latency
128k
Context
$0.004
Cost / req
Evaluation suite
Deploy pipeline
prod / canary 25% — healthy