Services

The AI Venture Studio That Ships
Products, Not Prototypes

Codiste is an AI venture studio. Since 2019 we've taken more than 150 AI products from whiteboard to revenue for founders, venture studios, and product teams across FinTech, RegTech, MarTech, and PropTech. Most AI projects die somewhere between the demo and the deployment. Ours don't.

A 30 minute call. A straight answer. No obligation.

  • American Airlines
  • IQM
  • Crush AI
  • RR Donnelley
  • Key AI
  • Hyundai
  • Infineon Wallet
  • Getin
  • Dialora AI
  • Cred Mantra
  • Area
  • Amplify
  • Assembler
  • Bioz
  • Bitopex
  • All Hands Together
  • ClassWizard
  • NDeck
  • Restate Copilot
  • BonFire - Bonfire Real-Estate Fractionalized Marketplace
  • Mesmr
  • CounterTen - Digital Collectible platform for Loyalty, Brands and events
  • Holygrails - Solana NFT Marketplace
  • CoinXpad - Coinxpad Decentralised Crypto Launchpad
  • Cypha - Make your Music using Cypha app
  • DiveWallet - Decentralised Safest Crypto and digital assets wallet
  • FTWDao - Diversifying the venture investing ecosystem
  • Medizen - Pill Reminder and Drug interaction Detection app
  • MLEstimation - AI Tool to Analyse your Building material
  • NearPro - Connecting Homeowner and top Contractor
  • Bloqhodler - Hedge fund investment app
  • zo
  • BrainPulses
  • NextGen
The studio model

We Build AI Products Like We Own Them

Because in a way, we do. A venture studio doesn't bill hours and walk away. We put our name on the outcome: the idea gets stress-tested before a single sprint is booked, the architecture gets designed for the scale you'll hit in year two, and after launch we're still around, tuning cost and reliability while the product earns.

Agencies sell time. Studios share outcomes. We picked the second model on purpose.
What we build

Three Things We Build, Properly

Each one ships into live operations, not a sandbox demo. Pick the closest fit, or bring us something in between.

An autonomous AI agent moving a task along a guarded path to a completed tray
01

AI Agent Development

An AI agent is software that finishes a job on its own: it reads the document, qualifies the lead, resolves the ticket, then hands you the log. That's what we build. Our agents run inside live operations at real companies, with guardrails and monitoring baked in from day one, so you always know what got handled and what got escalated.

A chatbot deflects work. An agent completes it. We only build the second kind.

What this covers

  • Autonomous workflow agents
  • Sales and lead qualification agents
  • Document intelligence and processing
  • Customer support resolution agents
  • Multi-agent orchestration
  • Guardrails, evals, and monitoring
Model outputs passing through a grading gate with pass and fail stamps and score gauges
02

AI Evals & LLM Evaluation

An eval is how you find out your AI works before your users find out it doesn't. It's the test suite for model behavior: does the agent answer correctly, cite the right source, stay inside policy, and do it at a cost you can live with?

Most teams ship on vibes and debug in production. We build evaluation systems instead: test sets drawn from your real data, automated grading pipelines, and regression gates that catch a bad prompt change before your customers do. Ship on evidence, not hope.

What this covers

  • Eval datasets built from real user data
  • LLM-as-judge and automated grading pipelines
  • Prompt and model regression testing
  • Hallucination and accuracy measurement
  • Red teaming and safety testing
  • Production monitoring and drift alerts
An AI orb assembling code blocks on a conveyor that passes a human review gate
03

AI-Native Development with AI-DLC

AI-DLC is the AI-Driven Development Life Cycle: a delivery method where AI does the heavy lifting of writing and testing code while senior engineers set direction, review every line that matters, and own the result. Work moves in bolts of hours and days, not sprints of weeks.

We build this way because it wins. Requirements get shaped with AI in the room, code ships the same day it's planned, and quality gates run continuously instead of at the end. Nothing merges without a human who understands it. That's how a validated concept reaches launch in weeks, on an architecture built to survive your Series A rather than be rewritten after it.

What this covers

  • Full AI-DLC delivery: bolts, not sprints
  • AI-generated code with senior engineer review
  • Requirements shaped with AI, validated by humans
  • Continuous testing and quality gates
  • Zero-to-one AI-native product builds
  • Moving existing codebases to AI-native delivery

How Does an Idea Become a Product Here?

Four stages. Every project, no exceptions, because every skipped stage turns into an invoice later.

  1. 01

    Validate

    One to two weeks of pressure-testing the idea against your market, your data, and what AI can honestly deliver today. Some ideas don't survive this stage. That's the cheapest possible time to find out.

  2. 02

    Architect

    Models, pipelines, infrastructure, and the cost curve, all designed and priced before any production code exists. You approve a blueprint and a number, not a running meter.

  3. 03

    Build

    Senior engineers ship something you can touch every week. Test it, redirect it, question it. You'll never sit wondering what your money did this sprint.

  4. 04

    Scale

    Launch is the halfway mark. We stay on to tune cost per query, harden reliability, and read the metrics that decide what gets built next.

Why Do Founders Pick a Studio Over an Agency?

An agency delivers the code you specify and bills for the time it took. A venture studio shares responsibility for whether the product works. That one difference shows up in three habits.

Scope and validation icon

We say no early.

Our first deliverable is usually a short list of things you shouldn't build. A week of validation costs less than a quarter spent building the wrong feature, and we'd rather trim scope than watch you miss a launch.

Ownership and handover icon

No black boxes.

Everything we build is yours, including the understanding of how it works. Documentation, knowledge transfer, clean handover. Your team should be able to extend our work without calling us. Most do.

Senior engineering methodology icon

Seniors from start to finish.

The engineers who scope your build are the ones who ship it. There's no quiet swap to a junior bench after signing. It's a large part of why 95% of our clients return with a second project.

Shipped, Live, and Earning

These aren't concepts. They're products with real users, and the case studies carry the metrics to prove it.

A voice platform

Holding thousands of concurrent calls in live production.

A creator AI tool

The kind people actually open every day, not once at launch.

A companion app

With retention numbers we're proud enough to publish.

Seven Years, Measured

We started in 2019. Here's the honest ledger, and the case studies that back it.

95%

Client retention
Clients who come back for a second build

150+

AI products shipped
From concept to production, 2019 to 2026

6-10

Weeks to MVP
From validated concept to launched product

What Working Together Actually Feels Like

No mystery about what the next few weeks hold. This is the rhythm, from the first call through launch and past it.

  1. 01

    A straight answer in week one.

    We validate the idea and tell you plainly what AI can and can't do for it. If the honest answer is "don't build this," you hear it now, not at month six.

  2. 02

    A blueprint you approve.

    Architecture, timeline, and the full build cost on one page before development starts. You commit to a number, not a meter.

  3. 03

    Working software every week.

    In your hands, ready to test and redirect. Progress you can click is the only progress that counts.

  4. 04

    We stay after launch.

    Cost tuned, reliability hardened, metrics wired in. Launch is where the product starts earning, so that's where we lean in hardest.

Who We Work With

Three kinds of teams, mostly, and one kind we politely turn down.

Venture studios
Running parallel builds, who need a partner that won't dilute quality across them.
Funded founders
Racing a runway, with users to reach before it runs out.
Product teams
Inside larger companies, done with proofs of concept that die in slide decks.
If you're shopping for the cheapest dev shop, that's not us, and we'll say so on the first call to save you the meeting.

Trusted Worldwide
Clients Who Built the Future

We build custom AI solutions for global innovators. We help clients-from fintech giants to disruptive startups-achieve transformative results, scale their business, and dominate their market.

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Let's Build the Future of Your Business Together

Partner with Codiste to transform vision into reality through AI, blockchain, and machine learning. Together, we'll build intelligent, secure, and scalable solutions that redefine what's possible for your industry.
Let's Build the Future of Your Business Together

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Get the Clarity You Deserve

Get answers to the most common questions about development, implementation, and ROI. If you don't find what you're looking for, our team is ready to help.

An AI venture studio is a team that builds AI products end to end, from strategy and design through engineering and launch, and shares accountability for the outcome instead of billing hours against a spec. That's the model Codiste has run since 2019.
An agency delivers the code you specify and charges for time. A studio like Codiste co-builds: the idea is validated before development, the architecture is designed for scale, and success is measured in users, revenue, and retention after launch.
At Codiste, a validated AI MVP typically ships in six to ten weeks. Production-grade agent systems for enterprise workflows usually take three to six months, depending on how ready your data is and how many systems we're integrating with.
It depends on scope, but you'll know the full number early. Codiste prices every engagement against a fixed validation stage first, so the complete build cost is on the table before you commit to it.
Codiste mainly builds AI products for FinTech, RegTech, MarTech, and PropTech companies, along with venture studios operating across those sectors.
Yes. Codiste embeds with in-house engineers, fills specific gaps, or runs the build end to end. Whichever route gets the product to market fastest is the one we'll recommend.
You do, fully. Code, models, and data pipelines built during a Codiste engagement belong to the client. No exceptions, no license-back clauses.

Talk to Experts About Your Product Idea

Every great partnership begins with a conversation. Whether you’re exploring possibilities or ready to scale, our team of specialists will help you navigate the journey.

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