$ git remote -v
vladchatware/vlad.chat
vlad.chat
Public relations agent
lang: TypeScriptstars: 0forks: 0
#mcp#claude#notion api#chat api
Applied AI Studio
We build custom
AI agents.
AI agents that can act autonomously, with humans in the loop when it matters.
Each one has a nervous system: context, memory, tool access. We scope it, build it, ship it — in under 6 weeks.
3
Live deployments
< 6 wks
Typical delivery
API + payments
Real integrations
Your next agent, taking shape.
# Built on production infrastructure
OPENAIANTHROPICMCPREMOTIONSTRIPENOTION
$ Capabilities
What we build
$ git remote -v
vladchatware/media.vlad.chat
media.vlad.chat
Remotion based Gen AI pipeline
lang: TypeScriptstars: 0forks: 0
#remotion#gpt-4o#social apis#stripe
$ git remote -v
vladchatware/music.vlad.chat
music.vlad.chat
Open AI DJ
lang: JavaScriptstars: 0forks: 0
#soundcloud#web audio#llm#three.js
$ Methodology
How an agent comes to life
boot sequence — agent lifecycle
- [01]
ScopeWe map the agent's environment.
Define capabilities, integrations, and data sources in a fixed brief. You know exactly what's being built — and what it costs — before we write a line of code.
- [02]
AnatomyWe design its nervous system.
Agent graph, API integrations, memory layer, output pipeline. You get a full architecture document before development begins.
- [03]
GrowthIt develops in weekly cycles.
Working demos from week 2. Continuous feedback loop until it behaves correctly in real conditions — not just the happy path.
- [04]
ReleaseIt goes live in your product.
Production deploy with monitoring, eval metrics, handover documentation, and a 60-day optimisation window after launch.
■ all checks passed — ready to deploy
$ Case Studies
Real AI agents in production.
Deployed for vlad.chat, media.vlad.chat, and music.vlad.chat.
| pid | type | agent | status | stack |
|---|---|---|---|---|
| 001 | Conversational | Digital Twin Terminal An AI character with memory and tool access Chat API + MCP (Notion) + Stripe checkout. It knows its context, references your knowledge base, and takes payments — all inside a conversation. No context switching. | Live | #mcp#notion#stripe#chat api |
| 002 | Content | Social Media Agent One prompt → five platform-ready formats Remotion-powered pipeline. Input a brief, get a story, carousel, tweet, thread, and video — formatted, rendered, ready to publish. No manual resizing. | Live | #remotion#gpt-4o#social apis |
| 003 | Media | Music Streaming Agent An AI DJ that reads the room Natural language music requests over a SoundCloud backend. Real-time 3D audio visualisation reacts to the track. Talk to it. It listens. It plays. | Live | #soundcloud#web audio#llm |
$ Social Proof
What they say after the demo.
> They didn't hand us a template and call it done. They built something that understands our product as well as our best people do. Six weeks, production-ready.
M. Chen
VP Operations, FinTech
> The agent is invisible in the best way — it just works. We stopped thinking about it as software and started thinking about it as a team member.
Dr. P. Nair
Chief Medical Informatics, HealthTech
> We evaluated four studios. jelly.ninja was the only one that came to the first call with a technical architecture sketch. That told us everything.
S. Delacroix
Head of Product, E-Commerce
$ Get Started
Commission your agent.
Tell us what you want to build. We'll scope it, price it, and ship it.
# Why teams choose jelly.ninja
- Fixed scope — written before we write code
- Production delivery — not a prototype or demo
- Live stack — vlad.chat, media.vlad.chat, and music.vlad.chat
$ agents.live
→ 3
$ avg_ship_time
→ 38 days
$ scope_changes
→ 0
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