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Industries · Crypto & market analytics

Crypto analytics platform development

Crypto data is fragmented and loud: prices live on exchanges, flows on chain, narratives in X and Telegram, funding news in a dozen feeds. Crypto analytics platform development is the work of turning those sources into answers people can act on — and showing where the sources disagree.

We built FOMO (fomo.cx): live market data, funding rounds, backers, token unlocks, OTC and NFT markets, launchpad projects and social buzz on one platform. FOMO AI answers questions from that data with the sources attached, and a consensus engine weighs sentiment, on-chain flows, exchange positioning and fractal patterns into one read per asset.

One backend serves the web platform, a mobile app, a Telegram Mini App and the admin. We build platforms like this at a fixed price under a contract, module by module.

Get a fixed priceTalk to the team →
Case
FOMOfomo.cx / crypto intelligence / 2026
Built
  • Product architecture
  • Data pipelines
  • ML and AI layers
  • Web platform
  • Mobile app
  • Telegram Mini App
  • Admin
Format
AI + DEV
Price
Fixed after scoping, paid by stage

Problems

What makes market data hard to use

  • Too many sources, all contradicting

    Exchanges, chains, social networks and news feeds each tell a different story. Users do not need more data; they need one read and the reason behind it.

  • AI that answers from memory

    An assistant that is not tied to your data invents prices and projects. In a market, a confident wrong answer is worse than none.

  • Models that change without warning

    A new model can shift every score overnight. Without quality gates and a trial period, users notice before you do.

  • Separate products drift apart

    Web, mobile and Telegram built on separate backends end up showing different numbers and different features.

What we build

What we build for market analytics

  • Data pipelines

    Market, on-chain, funding and social sources, each a module with its own model and quality gates.

  • Consensus score

    Signals from every module combined into one read per asset, with the places where they disagree shown, not hidden.

  • AI assistant on your data

    Answers only from platform data, with links to it, and says so when the data has no answer.

  • Shadow mode for models

    New models run in shadow before they are allowed to speak to users, so they are checked on live data first.

  • Web, mobile and Telegram

    One backend for the web platform, a mobile app and a Telegram Mini App, so every surface shows the same numbers.

  • Admin

    An admin for your team on the same backend as the web, mobile and Telegram products.

Case

How we built it for FOMO

FOMOfomo.cx / crypto intelligence / 2026

Crypto market intelligence in one place

The challenge

FOMO turns the noise of the crypto market into something a trader or an investor can act on. People needed one place that answers simple questions quickly: what is moving, who is behind a project, what unlocks next, and how much of the talk is real.

What we did

Every source became a module with its own model and quality gates, and the modules meet in one consensus that also shows where they disagree. New models run in shadow mode before they are allowed to speak, and the AI assistant answers only from platform data, with links to it.

Read the case →Live product

Three formats

Choose how we build it

The format decides who writes the code and how much engineering review goes into it — and with that, the price and the pace.

  • AI / build

    AI Build

    Fastest path · prototypes & internal tools

    AI generates the structure and most of the implementation. Engineers review integrations and the release. The lowest cost, for prototypes, internal tools and MVPs that test an idea.

  • AI / engOur pick here

    AI + DEV

    Recommended for most MVPs

    AI builds the scaffolding and the obvious parts. Engineers own the architecture, critical logic, integrations and full QA. Balanced pace and review, for customer-facing MVPs and B2B products.

  • full / eng

    DEV

    Maximum quality & control

    Senior developers own architecture and implementation end to end. AI is an internal tool for speed, never the final author. For production systems and regulated domains.

Analytics people act on belongs in AI + DEV: engineers own the data pipelines, model access and guardrails, and QA tests the failures, not just the happy path. An internal research dashboard can start in AI Build; add DEV where money moves.

FAQ

Questions we get asked

How much does a crypto analytics platform cost?

It depends on the sources, the models, the AI layer and the surfaces — web, mobile, Telegram. Each is a module in the estimate. Data providers’ and AI model usage fees are separate from the contract price and depend on traffic; we size them with you at the team review.

Which data sources can you connect?

Exchanges, on-chain data, funding and project databases, social feeds — any source with an API or a feed you are allowed to use. Each becomes a module with its own quality checks; the terms and fees of paid sources are agreed with you at the team review.

Will the AI assistant make things up?

It can, which is why we design against it: on FOMO the assistant answers only from platform data and links to it. When the data has no answer, it says so instead of guessing.

Can the platform work inside Telegram?

Yes. On FOMO the same backend serves a Telegram Mini App next to the web platform and the mobile app, so people reach it without an install.

Is this only for crypto?

No. The same architecture — sources as modules, a consensus score, an assistant grounded in data — suits other markets where many noisy sources have to become one clear read.

Who owns the platform and the models’ code?

You do, once the contract is paid in full: the source code, the documentation and the data. Third-party models and data feeds stay under their providers’ terms.

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