What we build
A few representative GenAI product directions — we adapt the approach to your specific idea.
Every project is shaped around the problem. These are starting points, not templates.
AI Research & Knowledge Tools
Typically combines search + RAG UX, agentic routing, and optional streaming with saved sessions.
Common use cases: internal search, research copilots, knowledge bases
AI Video Ads & Creative Automation
Systems designed to generate ad concepts, orchestrate avatar/voice steps, and handle async rendering.
Common use cases: ad variants, avatar/voice creatives, automated rendering pipelines
AI Short-Form Video Systems
Often involves script + TTS pipelines with non-blocking rendering and structured asset/output handling.
Common use cases: batch video generation, content pipelines, template-driven edits
Creator Analytics & Growth Tools
Designed for creator workflows like thumbnail ideation, competitor analysis, SEO planning, and content ops.
Common use cases: thumbnail ideation, SEO planning, competitor analysis
AI Branding & Design Tools
Typically includes prompt-led ideation, rapid iteration on design directions, and a clear version history.
Common use cases: logo directions, brand kits, iterative design exploration
Voice-First AI Interview Systems
Often includes dynamic question flows, structured scoring, and an operator-friendly review dashboard.
Common use cases: screening interviews, structured scoring, voice-first workflows
Have a different idea? Most GenAI MVPs don’t start in a neat category — and that’s okay.
You’ll work directly with the builder — from scoping to a shippable MVP.
How we work
A focused, low-friction process to ship a production-ready GenAI MVP you can own and iterate on.
Typical timeline: roadmap in 48 hours, then an MVP in ~2–4 weeks depending on scope.
1) Scope and acceptance criteria
This step can be engaged on its own as a dedicated scoping phase.
- Define the user goal and the specific job the AI must do
- Write “good output” examples and failure examples (what to avoid)
- Lock the MVP boundary: what’s in, what’s out, and what we won’t build yet
Output: A written scope, user flows, and acceptance criteria we can test against.
2) GenAI system design
- Decide how the system will ground answers: context, retrieval, tools, or human input
- Design prompts, tool schemas, and state with predictable failure handling
- Set budgets early: latency targets, cost guardrails, and rate limits
Output: A lightweight design for the workflow, plus an evaluation plan and guardrails.
3) Build real workflows (not demos)
- Implement the end-to-end path: inputs, orchestration, outputs, and review points
- Add guardrails: structured outputs, citations where needed, and safe fallbacks
- Instrument what matters: logs, traces, and error modes you can act on
Output: A working MVP with a real workflow, measurable quality, and clear operational behavior.
4) Production readiness + handoff
- Harden the workflow: retries, timeouts, idempotency, and safe degradation
- Set up basic monitoring and runbooks for the core failure modes
- Hand off ownership with clean docs and a prioritized next-steps backlog
Output: A production-ready MVP with clean ownership and a clear path to iterate.
Who We Work Best With
We partner with teams looking to ship production GenAI systems — not experiments.
Great fit
- Startups validating a GenAI product idea
- SaaS teams embedding AI workflows into existing products
- Founder-led teams wanting direct builder collaboration
- Teams comfortable iterating quickly with weekly feedback
Probably not the best fit
- Pure marketing content generation requests
- Large enterprise RFP-led vendor selection processes
- Fully fixed-scope builds defined upfront
- Projects requiring large outsourced dev teams
We intentionally take on a limited number of MVP builds at a time to stay deeply hands-on and maintain build quality.
Have a GenAI MVP in mind?
If you're planning to build a production GenAI system — not just a prototype — we can help you scope and ship it.
In a short discovery call, we'll align on scope, timeline, and the fastest path to a working version users can try.
No prep needed — bring your idea or rough concept.