Kruzeniski Studio · AI Product & Development

We also build the software.

The same team that runs the agent stack is a senior product studio. We help founders turn complex ideas, prototypes, and unfinished codebases into fast, reliable, production-ready software — AI web apps, full-stack SaaS, product rescues, and game platforms.

90+

API routes shipped

260+

automated tests

10

autonomous agents

23

table schemas

60+

route game hub

How our AI works

Software that takes real, bounded actions.

We architect agents that take real, verifiable actions — tool calls that mutate databases, multi-model pipelines, publishing flows — always behind validation and a human approval gate. The gate isn’t a limitation to apologize for; it’s the reason the automation is safe to adopt.

pipeline.ts · illustrative
// Beatwire publishing pipeline — illustrative
await radar
  .cluster(signals)        // group breaking stories
  .draft({ models: 4 })    // multi-model draft
  .review()                // automated checks
  .awaitApproval()         // ← required human gate
  .publish(channels);      // only after a human says yes

What We Ship

Four ways we ship software that works.

From new AI products to rescuing stalled codebases and building game platforms — one senior studio, honest scope.

AI

AI Application & Agent Development

Beyond chat bubbles — multi-agent systems, tool-calling workflows, knowledge-grounded generation, and voice pipelines that take real, verifiable actions.

  • Multi-agent orchestration & cross-agent handoffs
  • Function calling & tool execution against live databases
  • Shared workspace memory & knowledge bases (RAG)
  • Multimodal capture (screenshot / document-to-data)
  • Voice integration (browser STT & TTS)
  • Human-in-the-loop approval workflows & draft safety queues

Proof: Beatwire · Agentic Work OS · Kruzeniski.ai

FS

Full-Stack Product & MVP Builds

Turn early specs or wireframes into a fully functional, cloud-hosted SaaS with clean architecture you can keep building on.

  • Next.js App Router, React, TypeScript, Tailwind
  • PostgreSQL (Supabase / Neon) with typed data access
  • Clerk auth, RBAC, and multi-tenant security
  • REST & tRPC API development
  • Stripe / payment webhook architecture
  • Vercel serverless deployment & CI/CD

Proof: Agentic Work OS · Sweatbox · Beatwire

RX

Product Rescue & MVP Acceleration

Stuck with a broken MVP or unmaintainable AI-generated code? We audit, refactor, complete missing integrations, and push it across the finish line.

  • Codebase & architecture security audits
  • Database schema reconciliation & migration repairs
  • Authentication & state-management rewrites
  • Replacing broken API mocks with live handlers
  • UI/UX polish & responsive layout refactor
  • Accessibility compliance & screen-reader overhaul

Ideal for: Founders with stuck projects or tight launch deadlines.

GS

Game Systems & Companion Hubs

Modern games live beyond the executable — game UI, strategy manuals, stat trackers, web companion hubs, and interactive AI-character experiences.

  • Unity C# gameplay systems, UI, & dynamic menus
  • Multi-route web companion platforms
  • Field manuals, item databases, loadout builders
  • Battlelog match histories & stat-tracking UIs
  • In-world AI NPC and operator chat
  • Marketplace and collection explorers

Proof: Grunts · World War 0x · Curfluffle

How We Work

Predictable milestones, clean code.

01

Technical discovery & architecture

We analyze your requirements, data model, and integrations, then deliver a clear technical spec, route map, and schema before writing code.

02

Foundation & auth setup

We stand up the repository, design system, database connections, and authentication boundaries to guarantee secure multi-tenancy.

03

Core workflow & AI integration

We build the main interfaces and wire up real model calls, tool handlers, and endpoints — focused on state persistence and real database mutations.

04

QA & accessibility polish

We run typechecks, tests, and screen-reader verification — visible focus, high contrast, and responsive mobile layouts.

05

Production deployment & handoff

We deploy to Vercel, configure DNS and SSL, set up crons and webhooks, and hand over complete documentation.

Engagements

Scoped by engagement, not public price lists.

Every estimate is tailored during a short discovery conversation.

1–3 weeks

Focused Build Sprint

Add a specific AI feature, build a dashboard, or resolve code debt.

4–8 weeks

Complete MVP Build

Turn an approved spec into a launched, production-ready product.

2–4 weeks

Product Rescue & Launch Pass

Audit, refactor, and launch an existing messy repo.

Retainer

Ongoing Development Partner

Dedicated weekly capacity for continuous iteration and scaling.

Why Us

Senior product thinking. Hands-on execution.

AI that stays in bounds

Safety queues, human-in-the-loop review, and strict tool-execution boundaries in every product. The system refuses to act unilaterally — and clients trust it more for it.

Accessibility-first

Built and tested with a screen reader from day one. Visible focus, semantic structure, and real keyboard paths — which turns out to help everyone.

Direct senior access

No account managers, no telephone game. You work with the builder — senior product thinking and hands-on execution, without the agency bloat.

Selected Work

Real products, shipped.

A family of AI apps, platforms, and games — each built and run by this team, each sharing the same bounded-action architecture. Open any one for the full build story.

View all case studies →

Guides

How agentic software actually works.

Plain-language explainers on each piece — the agent loop, integrations, grounding, on-brand output, and how we build it — using our own projects as the worked examples.

Agentic foundations · 6 min

How agentic AI actually works: the tool-calling loop

“Agentic” gets used loosely. Underneath, it's a specific, understandable loop: the model proposes an action, your code runs it, the result goes back in. Here's the whole mechanism, plainly.

Read the guide →

Agentic foundations · 5 min

From chatbot to operator: designing AI that takes safe actions

The gap between a demo and a product is safety. Here's the pattern we use to let an AI change real data — typed tools, server-side validation, and an approval gate — so it's capable without being reckless.

Read the guide →

Architecture · 6 min

Building a multi-agent stack: how ten agents share one brain

Ten agents that each start cold produce ten disconnected snippets. The trick to output that feels like one team is shared context and structured handoffs. Here's how the stack is wired.

Read the guide →

Integrations · 5 min

Connecting social accounts the right way: OAuth, encryption, and manual-confirm posting

Posting to X, Facebook, and LinkedIn from an app means holding the keys to someone's audience. Here's how we do it safely: scoped OAuth, encrypted tokens at rest, and a posting flow that always ends in a human click.

Read the guide →

Integrations · 4 min

One pipeline, many destinations: publishing to WordPress, Ghost, and newsletters

A story that's ready shouldn't need re-formatting for each platform. Here's how a single pipeline pushes finished content to WordPress, Ghost, and email — with the same approval gate in front of every destination.

Read the guide →

AI engineering · 5 min

Grounding AI in real data: live crawling and RAG vs. stale training

A model's training data is frozen in the past. For anything about the live web — your site, your rankings, today's numbers — you have to feed it fresh context. Here's how grounding works and when to use which kind.

Read the guide →

AI engineering · 5 min

Keeping AI on-brand: voice profiles, canon, and shared context

Generic AI output reads generic. The way to make it sound like you — or stay true to a fictional universe — is to make consistency a system feature, not something a person has to remember every prompt.

Read the guide →

AI coding · 6 min

How we build fast with AI coding — the workflow behind these apps

These products were built by a small team moving quickly with AI in the loop. Speed like that only works with guardrails. Here's the actual workflow — specs first, tests always, human review at the edges.

Read the guide →

Architecture · 5 min

Running agents on a schedule: cron, routines, and draft-first automation

An agent you have to trigger by hand isn't really a worker. Here's how we let agents run on their own each day — producing drafts on a schedule — without ever crossing the line into acting unsupervised.

Read the guide →

Start a Project

Ready to turn your idea into a working product?

Tell us what you're building, the code you have, or the problem you need solved. We'll reply within 24 hours with practical next steps.

Start a project
Kruzeniski Studio — AI Apps, Platforms & Games · Kruzeniski.ai