AI Engineering
Production AI systems with retrieval, tool use and orchestration — designed for reliability, not demos.
AI-Native Engineering Company
Berako Technologies builds AI-powered products, intelligent automation, scalable cloud platforms, fintech infrastructure and Web3 systems designed for real-world scale.
United States · Europe · Worldwide
The Berako Core diagram represents our engineering system and the capabilities connected to it:
Berako Technologies is an AI-native software engineering company that designs and builds AI systems, intelligent automation, scalable software, cloud platforms, fintech infrastructure and Web3 applications for companies worldwide.
Platforms and protocols our engineers build with. These are technology ecosystems, not client relationships.
End-to-end engineering
Berako combines AI, software, cloud and financial infrastructure to build systems from concept to production.
Production AI systems with retrieval, tool use and orchestration — designed for reliability, not demos.
Backend platforms and services built on clean architecture, strong typing and well-defined contracts.
Infrastructure that scales predictably, deploys safely and tells you what it is doing.
Financial systems where correctness, auditability and security are the product requirements.
On-chain systems and the off-chain infrastructure that makes them usable at scale.
AI-native process
We use AI at every stage of engineering — for exploration, generation, review and monitoring. Senior engineers stay accountable for architecture, security and every technical decision that ships.
AI accelerates research; engineers define the real problem.
Models explore options; architects choose and own the design.
AI-assisted development under strict review and typing.
Generated coverage plus deliberate adversarial testing.
Automated pipelines with progressive, reversible releases.
Continuous monitoring turns production signal into changes.
System design that scales
A product is only as good as the system underneath it. We design the whole path — product architecture, service boundaries, data models, cloud infrastructure and, where it applies, financial and blockchain integration.
That means clear contracts between services, data that stays consistent under load, infrastructure defined in code, and observability built in from the first deploy rather than added after the first incident.
User / Client
API Gateway / Edge
Auth
Core Services
AI Agents
Data Services
Data Layer
Cloud Infrastructure
Blockchain / Financial Infrastructure
Selected work
Representative engineering problems and how we approach them. Detailed case studies are published as clients approve them.
View all projectsFintech platform
PlaceholderPayment flows that must stay correct and auditable while throughput grows.
Event-driven services with idempotent transaction handling, reconciliation, and end-to-end tracing across every money movement.
AI automation
PlaceholderOperational workflows that depend on unstructured information and manual judgement.
Multi-agent orchestration with retrieval over internal knowledge, tool integrations into existing systems, and evaluation harnesses that gate every release.
Web3 infrastructure
PlaceholderOn-chain systems that need to be secure, upgradeable and usable by non-crypto-native products.
Audited Solidity contracts, oracle integration, custody-aware key handling, and indexing infrastructure that exposes chain state through ordinary APIs.
Engineering insights
Practical writing on the systems we build — architecture decisions, trade-offs and what production actually teaches you.
View all insightsAI engineering
PlannedEvaluation, guardrails and failure handling — the parts of agent systems that decide whether a prototype ever becomes a product.
Cloud architecture
PlannedService boundaries, back-pressure and graceful degradation patterns for high-availability distributed systems.
Data & platforms
PlannedWhy retrieval quality is a data engineering problem, and how to build the pipelines and governance that make it work.
Frequently asked questions
What Berako does, how we work, and how a project gets started.
Berako Technologies is an AI-native software engineering company. We design and build AI systems, intelligent automation, custom software, scalable cloud platforms, fintech infrastructure and Web3 products — from initial architecture through to production operation.
Yes. We build agent systems that use large language models with retrieval-augmented generation over your own data, tool and API integrations into existing systems, and orchestration across multi-step workflows. We treat evaluation, guardrails and observability as part of the build, not as an afterthought, so agents behave predictably once they are handling real work.
Yes. We work remotely with companies across the United States, the United Kingdom, Spain, Portugal, France, Malta and the wider European market, as well as international clients elsewhere. Engagements run on overlapping working hours, shared repositories and documented architecture decisions, so distributed collaboration is the default rather than an accommodation.
Yes. Modernization is a common starting point. That typically involves mapping the current architecture, introducing clear API boundaries, decomposing monolithic components into services where it genuinely helps, migrating workloads to cloud infrastructure defined in code, and integrating AI capabilities into existing products. We work incrementally so the platform keeps running throughout.
Yes. On the fintech side we build financial platforms, payment and transaction infrastructure, and secure integrations with third-party financial services. On the Web3 side we develop smart contracts in Solidity for EVM chains, blockchain infrastructure, oracle integrations and digital-asset systems. Both require the same discipline: correctness, auditability and security by design.
It starts with a technical discovery call to understand the problem, the constraints and what success looks like. From there we produce an architecture proposal covering the recommended approach, the technical trade-offs and a delivery plan. Once that is agreed, execution begins in short iterations with working software reviewed throughout.
Let’s build what’s next
Let’s engineer the future together.