We build intelligent products, AI systems, and scalable technology that drives real business outcomes.
Most engagements blend all four. An AI model needs a product around it, automation needs pipelines, on-chain logic needs an audited core.
LLM agents, RAG pipelines, computer vision, and MLOps. Production AI that holds up under real traffic and real accountability.
Learn more →Workflow orchestration, ETL pipelines, and system integrations that delete manual steps and keep your data flowing reliably.
Learn more →Full-stack teams that design, build, and scale web and mobile products end to end with a founding-team mindset.
Learn more →Audited smart contracts, dApps, and Web3 infrastructure on Ethereum and Solana — security-first, gas-aware by default.
Learn more →AI products, agents, and on-chain experiences built end to end — from first conversation to live launch.
All case studies →
The world's first AI assistant for Solana Mobile, turning complex Web3 actions into a simple conversation.

The AI architecture protocol and agent marketplace on Solana, turning tokens into living, community-driven characters.

An AI character agent that turns X mentions into AI-generated visuals through an end-to-end ElizaOS and Gemini pipeline.
"DROX built our entire Solana Mobile AI stack from scratch. The depth of knowledge they brought — across AI, Web3, and mobile — was unlike any team we'd worked with before."
"The transparency throughout the project was genuinely refreshing. Weekly demos, live dashboards, and honest status updates. No surprises at launch."
"We came with a rough idea for an on-chain agent launchpad. DROX turned it into Tars — a fully working marketplace with real social presence on Solana."
"Working with DROX felt like having a co-founder embedded in the team. They challenged assumptions, moved fast, and shipped a product we're genuinely proud of."
"Our automation backlog was years old. DROX scoped it, prioritised the highest-leverage workflows, and had live pipelines running within the first month."
Perspectives on AI engineering, on-chain systems, and building software that lasts.
Shipping an LLM without an eval harness is like deploying without tests. Here's how we build eval pipelines that catch quality regressions before users do.
A pre-mainnet audit isn't a checkbox. We walk through the patterns we look for and the missteps that make contracts exploitable under real conditions.
We've seen teams automate the wrong things. The compounding wins come from boring, high-frequency processes — not the exciting ones.
Tell us what you're solving. We'll come back with a point of view, not a sales script.