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New projects
A paragraph about the problem is enough to start. We reply within two working days, usually with questions rather than a quote.
Insights Guides and notes from the build.
AI agents, RAG, MCP, smart contracts, exchanges and chain abstraction — explained by the engineers who build them, for the people who buy them.
What an AI chatbot costs to build and run
The model is rarely the big line. Your data, the systems the chatbot must act in, and the testing that proves its answers decide the budget.
What an MVP costs to build, and how to spend less
An MVP costs what its scope costs. The cheapest first version is the one that tests your riskiest assumption with the fewest screens.
What a mobile app costs to build and keep running
Screens are the visible part. The backend, offline behaviour, integrations and store releases decide what a mobile app costs.
Outsourcing software development to India: a buyer's guide
Fixed project, dedicated team or staff augmentation — how to choose a model, check a partner, and keep ownership of your code and keys.
Chain abstraction vs account abstraction: what is the difference?
Account abstraction makes one account programmable. Chain abstraction makes many chains feel like one. How they differ, and why one needs the other.
Intents and solvers: how cross-chain apps really move value
An intent is a signed outcome, not a list of transactions. Solvers compete to deliver it. How intent systems work, where they fail, and what to check.
ERC-7683 explained: the cross-chain intents standard
ERC-7683 gives solvers one way to read orders from many intent protocols. What the current draft defines, what changed, and what it leaves to you.
Chain abstraction vs cross-chain bridges
A bridge moves assets between chains. Chain abstraction hides the chains from the user, and still relies on bridges, solvers or messaging underneath.
How to add chain abstraction to an existing dApp or wallet
Start from the journeys where users hit a chain boundary, choose established building blocks, design for unfilled intents, and launch with limits.
What chain abstraction costs to build
The number of chains, the journeys you abstract, the build-or-integrate choice and the security work decide what chain abstraction costs.
What a crypto exchange costs to build
The matching engine is the small part. Custody, compliance, liquidity and operations decide a centralized exchange budget; audits decide a DEX.
What a smart contract audit costs, and why
Audit price follows the amount and complexity of code, not the value it will hold. How scope and readiness move the number, and how to spend less.
What it costs to tokenize a real-world asset
The token contract is the small part. Legal structure, investor onboarding, custody, the register and ongoing administration decide the budget.
What custom HRMS software costs to build
Module count is a poor guide. Payroll rules, attendance hardware, integrations and data migration decide what an HR system costs to build.
MCP is settled. Permissions are the hard part.
The Model Context Protocol settled how agents connect to tools. What is left is the unglamorous half: scopes, rate limits, trust boundaries and audit trails.
What agent evaluations actually catch
Benchmarks tell you how a model ranks. A useful evaluation suite tells you whether last week's change broke something your customers rely on.
Tokenized assets: the boring parts are the project
Issuing the token takes a week. Transfer restrictions, investor eligibility, key loss and the legal register are the rest of the work.
Passkey wallets: recovery is the real work
Passkeys removed the seed phrase from onboarding. The design effort has moved to what happens when a user loses the device that holds them.
Prompt injection: scope the tools, not the prompt
An agent with tools is an agent with a blast radius. Filtering text does not hold; limiting what the agent can do does.
What an AI agent costs to build and to run
The model bill is rarely the biggest cost. Build effort goes into integration and evaluation, and running cost can be measured before launch.
Preparing for a smart contract audit
Auditors are paid by time. Code that arrives frozen, specified and tested lets them spend that time on the problems that matter.
How to choose a blockchain development company
Rankings tell you who is large. These questions tell you who will keep your users' funds safe and hand you code you can own.
Custom HRMS or off-the-shelf HR software?
Most companies should configure an existing HR system. Some should build. The deciding factors are your policies, your integrations and your workforce.
What is agentic AI? A practical guide for businesses
Agentic AI systems do not just answer — they plan, use tools and act. What that means in practice, where it works today, and what to put in place first.
RAG vs fine-tuning: which does your AI project need?
Retrieval gives a model knowledge; fine-tuning teaches it behaviour. How to tell which problem you have, and why many systems use both.
How to build an AI agent: a step-by-step guide
From choosing the task to production rollout: the steps that turn an AI agent demo into a system you can trust with real work.
What is the Model Context Protocol (MCP)?
MCP is the open standard that lets AI assistants and agents use tools and data. What it is, how it works, and what it means for your business systems.
How AI is changing HR, attendance and payroll
Practical uses of AI in HR today — from answering policy questions to catching attendance anomalies — and the safeguards employee data demands.
What is chain abstraction? One app, every chain
Chain abstraction removes network switching, bridging and gas juggling for users. How it works — accounts, intents, solvers, messaging — in 2026.
AI use cases that work in business today
Ten practical AI use cases — from support and documents to sales and engineering — with what each needs to succeed and where to start.
How to choose an AI development company
Every agency now offers AI. These questions separate teams that can ship a reliable AI system from teams that can only demo one.
06 / Let’s build
Bring us the difficult problem.
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Careers
Engineers, designers and researchers who like systems that are hard to get right. Send something you built and what you would change about it now.
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Studio
Based in India and working remotely, with overlap hours agreed up front so your team always has a time to reach us.
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Read
Guides on AI agents, RAG, MCP, tokenization and chain abstraction, written by the engineers who build them.