Local proof
Start with one product surface your team already owns instead of a broad transformation plan.
Boulder AI design system readiness
Local AI teams need design systems agents can actually follow.
Aktive helps Boulder, Longmont, and Colorado software teams turn product design knowledge into AI-ready system rules, component mappings, review gates, and proof packets before agent-assisted UI work drifts from the real product.
$2,995/mo
One active request
Pause between requests
Best for
- Boulder and Longmont AI startups adopting AI coding tools.
- Colorado SaaS teams with product UI, design-system, or handoff drift.
- Founder-led teams that need a proof packet before investing in a bigger design-system effort.
Common outcomes
- AI-ready rules for one real product surface.
- Token, component, and Figma-to-code mapping gaps.
- Human review gates and proof evidence for local product teams.
Source-linked proof
Public work before private claims.
conversion flow
Consumer conversion flow
Aktive can tighten a buyer-facing flow around the next action without reducing it to a generic landing page.
Inspect source
healthcare workflow
Healthcare product workflow
The work can make sensitive, high-context product workflows readable without leaning on AI hype visuals.
Inspect source
product ui
Product UI breadth
Aktive can handle high-information software surfaces while keeping hierarchy and review paths clear.
Inspect source
Local product teams
Boulder has AI momentum. Most product systems are not ready for agents.
The risk is not that teams lack tools. The risk is that agents work from partial design memory, scattered Figma files, vague prompts, and code conventions nobody has translated into a usable operating packet.
Agent context
Turn product, design, and engineering rules into instructions an AI assistant can use before it changes UI.
Human control
Keep risky changes behind review gates with screenshots, tests, decisions, and evidence.
Decision support
What to decide before booking.
Use this page to decide whether the first request is concrete enough for a focused monthly lane.
Strong first request
Review one live product or launch surface and identify where AI agents would likely break the design system.
Strong first request
Create an agent-readable design-system packet from existing Figma, code, docs, and product decisions.
Boulder / Longmont focus
The first local wave targets nearby AI, SaaS, and software teams where a founder, product lead, designer, or engineering lead can evaluate a focused sprint quickly.
Compared with local agencies
This is not a broad redesign pitch. It is a focused design-system and agent-readiness packet for one real product surface.
FIT CHECK
When this is not the right lane.
Aktive is intentionally narrow. Clear boundaries make the work faster, cleaner, and easier to review.
Teams looking for generic AI strategy without product/design-system proof.
Teams with no product surface, Figma file, codebase, or existing design language to inspect.
Fully autonomous AI workflow promises with no human review.
Broad enterprise transformation before one useful local proof packet exists.
PLAIN ANSWER
Aktive offers a local AI design-system readiness sprint for nearby AI, SaaS, and product teams that want faster agent-assisted work without losing design-system control.
Do you work with Boulder and Longmont teams?
Yes. Aktive Design is based in the Boulder area and works remotely with software teams, with a local lane for Boulder, Longmont, Boulder County, Denver, and Colorado product teams.
What makes this different from a normal design-system audit?
A normal audit explains gaps. This sprint turns one product surface into agent-readable rules, component and token guidance, Figma-to-code notes, review gates, and proof evidence.
Who is this for locally?
It is strongest for Boulder/Longmont AI startups, B2B SaaS teams, product-led service companies, and engineering-led companies adopting Cursor, Codex, Claude Code, Figma MCP, or similar tools.
Do we need a complete design system?
No. The sprint works well when the system is partial, messy, or mostly tribal knowledge, as long as there is a real product surface to inspect.
CHOOSE BY NEED
Use these routes as a decision path before booking the fit call.