Question 1

How long does a typical engagement take?

Accepted Answer

Most builds go from zero to production in 6 weeks.  Week 1 you get real, deployed software you can click through — running on actual infrastructure, not a static mockup or design file. From there: auth and data in Week 2, AI features in Week 3, cost controls and guardrails in Week 4, UX polish and load testing in Week 5, and a production launch in Week 6. Larger systems get scoped into phases, but the first phase always ships fast.

Question 2

Do we own the code at the end?

Accepted Answer

Yes, fully. Every line of code, every design asset, every configuration — it's yours the moment it's written. No proprietary frameworks, no vendor lock-in, no licensing fees. You can take the codebase to any team and keep building.

Question 3

Can you work with our existing codebase?

Accepted Answer

Yes. We regularly step into partial builds, legacy systems, and codebases mid-flight. We'll audit what's there, identify what's worth keeping, and build forward from that — no "you have to start from scratch" pressure.

Question 4

What makes your AI features production-ready vs. a demo?

Accepted Answer

Demos only need to work once. Production needs to work for thousands of users, control costs, handle edge cases, and recover gracefully when a model fails. We build evaluation suites to catch regressions before they reach users, guardrails to block bad outputs, and fallback chains for when a primary model is unavailable. Concretely, that means defined fallback behavior on every AI call and regression checks on every release — not a system that works in the demo and breaks in the wild.

Question 5

Do you handle the full stack or just the AI layer?

Accepted Answer

The full stack. AI only works when auth, data pipelines, UX, and infrastructure are handled correctly too. We handle all of it — APIs, database schema, authentication, real-time systems, deployment, and the AI layer on top. No handoffs, no finger-pointing between teams.

Question 6

How do you keep AI costs predictable?

Accepted Answer

We build cost controls into every AI product from day one: prompt versioning, token usage monitoring, per-user and per-feature spending limits, and fallback models for when costs spike. You get clear cost visibility and alerts before launch — so spend never moves without your knowledge — not a surprise invoice after.

Question 7

What if we're not happy with the work?

Accepted Answer

We operate on milestone-based delivery — you see working software at the end of every week, not a big reveal at the end. If something isn't right, we fix it before moving to the next phase. And if we ever fall short of what was agreed, we make it right — whether that means additional work at no cost or a partial refund. We'd rather earn a long-term relationship than defend a bad deliverable.

Question 8

What does post-launch support look like?

Accepted Answer

We don't disappear after launch. Every engagement includes a stabilization period where we monitor, fix, and iterate based on real user behavior. Long-term, we offer retained partnerships for teams that want Scryptflo on-call — ongoing features, infrastructure scaling, and AI model updates as the ecosystem evolves.

Question 9

How do we get started?

Accepted Answer

Send us a message through the contact form. Describe what you're building, where you're stuck, or what you want to launch. We reply within one business day, and if there's a fit, we'll set up a call to map out scope, timeline, and a plan to get to Week 1 software fast.

We turn the
noise into a flat line.

Idea to production in 6 weeks.

From design
to development.

AI

From 2008 to a site that closes deals.

✦ Welcome to ScryptCo ™ ✦

Software, with intent.

Questions, answered.

Tell us what
we should build.

We turn the noise into a flat line.