Generic Dev Shops Miss the AI Layer
Most agencies build CRUD apps and call it done. They do not know how to integrate LLMs with structured outputs, build RAG pipelines that retrieve correctly, or ship AI agents with real guardrails.
We build AI-powered SaaS platforms, mobile apps, and full stack web applications for startups and scale-ups that need software which actually holds up when real users arrive.
It is not a technology problem. It is an execution problem. Most teams build what looks good in a demo and discover the gaps when real users arrive.
Most agencies build CRUD apps and call it done. They do not know how to integrate LLMs with structured outputs, build RAG pipelines that retrieve correctly, or ship AI agents with real guardrails.
The prototype impresses in a meeting. Production breaks because there are no structured outputs, no retry logic, no cost controls, and nobody watching when the model drifts. Users stop trusting it after one bad response.
V1 ships. The founder demos it. Then it breaks on edge cases nobody anticipated and the team that built it has moved on. The product is technically delivered but not production-ready.
The result
Teams spend months building software that passes the demo and fails the first month of production. The agency moves on. The founder concludes the technology does not work. The technology is fine. The execution was not.
Every service exists because a client needed it shipped to production, not because it looked good on a brochure.
For products that need AI that actually works in production.
For teams that need a complete product built end-to-end.
For products shipping to iOS and Android simultaneously.
For teams building multi-tenant software that scales.
For teams replacing manual workflows with intelligent automation.
For teams that need reliable, documented APIs under their product.
Not sure where to start
Most of our best work starts with a conversation about your problem, not a predefined service. Tell us what is not working and we will say honestly if we can help.
Most agencies start with a requirements document and end with a product that works in demos. We start with architecture and ship testable software by the second week.
Most engagements: 6 to 14 weeks from scoping to production
STEP 01
We understand your domain, stack, and goals before writing code. We define the data model, API contract, auth design, and AI boundaries. These decisions are cheap to make now and expensive to change after the product is built.
You get an architecture doc your team can build against, not a vague requirements list.
STEP 02
We move fast without moving recklessly. The second week delivers something deployed and testable: a working endpoint, a UI prototype, or a functional AI pipeline. Not a Figma deck.
Progress you can see and test, not promises about progress.
STEP 03
We own the full stack: frontend, API, AI layer, and third-party integrations. Everything is wired and tested with realistic data before handover. Nothing gets delivered that only works in a demo.
Production-ready software, not a polished prototype.
STEP 04
We stay involved after go-live. Products need to evolve with real user behavior and new feature requirements. A system that works on launch day needs to keep working six months later.
We do not disappear the week after you go live.
The result
Software built from a spec sheet solves the problem the client described. Software built from inside the problem solves the problem the client actually has.
We started as full stack developers and got pulled deeper into AI when clients kept asking us to make it work in production, not just in the demo.
Full stack and AI engineering with production experience in Next.js, React Native, FastAPI, Rails, and AI integrations including Claude, OpenAI, and RAG pipelines.
Working with startups and scale-ups globally, building from zero or adding AI to existing products.
Claude AI · OpenAI · RAG · React Native · Next.js · FastAPI · Rails
We have been shipping LLM features into production since GPT-3 was new. RAG pipelines, AI agents, voice AI, and structured outputs, built and monitored in real products, not demo environments.
You are not our first AI integration project.
20+ production applications shipped. React Native, Next.js, FastAPI, Rails, PostgreSQL. The full stack is owned end-to-end. Reliability under real user load is what you are buying.
What we deliver runs in production, not demo environments.
Frontend to database. We own the entire stack so there are no seams between the front-end team and the back-end team. One codebase, one team, one point of accountability.
No blame cycles. We own it all.
Financial SaaS, mobile commerce, mortgage AI, real estate analytics, crypto trading, voice journaling. AI features need to work inside actual business logic, not just against toy datasets.
We fit the problem, not a generic product template.
The result
Clients hire agencies that sound technical in a sales call. They need a team that has shipped the same type of product before. That is the only kind of team we built Glitch Devs to be.
Not every project is the right fit for how we work. Here is who we work best with, and what that looks like in practice.
You have a product idea and need a technical partner who can build it right from the start, not a dev shop that delivers mediocre CRUD and calls it a product.
Production-ready software from the first sprint, not from the third rewrite.
We can help if
Your agency has design and product capacity but needs a development team with real AI and full stack expertise. You need a partner who can execute, not a vendor who needs managing.
White-label development your clients will not outgrow.
We can help if
Your product works and has real users. Now you need AI-powered features but your current team does not have the LLM expertise to ship them safely and reliably in production.
AI features that land in production and stay there.
We can help if
Not sure if you are a fit
If your project does not fit these three categories, tell us anyway. Some of our best work started that way.
No sales process. No pitch deck. A direct conversation about your situation and whether we can help.
How we respond
We read every message properly and reply within one working day, with a direct answer or a short call if the problem needs it. No automated sequences. No SDR handoffs.
Good reasons to reach out
We respond within one working day.
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