Find the real problem.
Map the people, data, and constraints. Define what a useful outcome actually looks like.

Angkasa Bestari Intelegensia builds AI agents, on-chain systems, and practical digital products. Our work connects market intelligence, industrial analysis, and everyday workflows?from research to a working interface.
Complexity in.
Clarity out.
AI & analytics + On-chain systems + Industry tools + Web & mobile
Our practice combines research, software engineering, and product design. We turn domain knowledge into tools that collect data, explain decisions, and support real workflows.
Find the right starting pointSpecialist-agent orchestration, language-model analysis, and model-powered interfaces. Work includes the THEMIS research desk, social-signal classification, and the Kronos forecasting integration.
Market-data pipelines, open-interest and volume scanners, regime analysis, backtesting, and paper-trading tools. Built to investigate hypotheses and make uncertainty visible.
Order books, smart-contract escrow, NFT mechanics, launchpads, wallet analytics, and payment integrations. Experience spans EVM networks and Solana, including testnet prototypes.
Domain-specific screening and decision interfaces for carbon capture and storage, tokenised carbon workflows, and technical research. Assumptions and calculation boundaries are made explicit.
Android apps, responsive business tools, dashboards, and interactive 3D experiences. Examples range from an instructor companion to a location-based collection game and small-business record keeping.
API integrations, scheduled bots, service monitoring, RPC caching, and deployment workflows. Practical infrastructure keeps data moving and makes system behaviour observable.
A selection from an ongoing practice of research, prototypes, and working applications. Each project explores a concrete problem.
Selected examples from our project portfolio. Project maps are illustrative. Research, demos, testnet implementations, and production tooling are identified by their documented scope.
Useful systems need more than a clever model or a polished screen. They need a clear path from the problem to everyday use.
Map the people, data, and constraints. Define what a useful outcome actually looks like.
Bring models, APIs, on-chain sources, and interfaces together around that outcome.
Turn the architecture into a working prototype with visible behavior and clear boundaries.
Evaluate what works, surface what does not, and improve through measured iteration.
One engineering practice.
Many useful applications.
An AI workflow, an on-chain product, an industry tool, or a mobile experience.
Start with the problem you want to solve.