AI Enablement · Software Engineering · Digital Transformation

We engineer AI into business.

Sinew is the tissue that connects strength to motion. Sinew Labs is that connection for your business — the engineering team between what AI can do and what actually ships, embedded in your team and shipping in weeks, not quarters.

Start a project → See how Rootstock works

Forward deployed, not outsourcedOur engineers work inside your tools and your sprint — not behind a ticket queue.

01 — The problem

Most of this isn't a technology problem.

It's a connection problem — between what AI can already do and what's actually running in your business. Sound familiar?

Someone re-types the same data into three different tools every morning.

Your best support answers only live in one person's head.

You've talked to four AI vendors and still don't have anything running.

Your "CTO" is a founder wearing a hat they didn't ask for.

New hires take two weeks to learn things a document should already know.

You're paying for software licenses nobody on the team actually opens.

That gap is what Sinew Labs is built to close. Here's how.

02 — How we help

What we do

Four areas, one engineering team, closing that gap from whichever side you need first.

AI Implementation & Enablement

Agentic workflows, RAG, and LLM integration — plus accelerators like Rootstock that get you running fast, and the training that lets your own team keep it running.

Custom Software Engineering

Full-stack build capability for the systems AI plugs into — CRMs, internal tools, integrations — not AI bolted onto duct tape.

Cloud & Platform Modernisation

Migrating, consolidating, and hardening the infrastructure underneath, so new AI capability has a stable platform to run on.

Forward Deployed Engineering

Senior engineers embedded directly inside your team and your tools, translating business problems into shipped systems — not a ticket queue.

03 — Who we are

The person behind Sinew Labs

One accountable engineer behind all four areas — not a committee, and not an offshore team you'll never meet.

Vikrant

Founder & CTO

Twenty years in software engineering, the last few spent building applied AI systems — LLM integration, agentic workflows, and production RAG. Sinew Labs is where that experience becomes AI implementation, software engineering, and engineers embedded directly in your team — not another vendor's slide deck.

20 years in software Applied AI engineering Fractional CTO

04 — How we're different

Why Sinew Labs

Traditional software vendors hand you a spec. We hand you outcomes — the same standard whether the work is AI, platform, or code.

Less handover

Your team works alongside ours from day one — not six months after a spec and a offshore build.

Weeks, not quarters

Rootstock is a starting point, not a blank repository. Configuration beats construction.

Built to be understood

Every agent decision is traced, costed, and explainable — your team can see exactly why an answer came back the way it did.

05 — Case study

Rootstock: this way of working, shipped.

Everything above is easier to say than to run. Rootstock is where we prove it — a retrieval foundation, an agent framework, and the operations layer to watch both, built the way we just described and now the first of our reusable accelerators.

Built on:

LangGraph pgvector Langfuse WorkOS (OIDC/SAML) LiteLLM Terraform

Knowledge base

Retrieval, out of the box

Upload documents, version them, keep them current — SSO from day one, a vector store fine-tuned per client, and a chat interface for domain Q&A.

Agentic workflows

An ontology for your domain

A base framework for entities, relationships, and rules — the same framework whether it's a café or a sports club.

LLM ops

A dashboard, not a black box

Cost, latency, and behavior tracked from the first query, built on Langfuse-style tracing.

Domain ontology

Chat window

Owner asks

Rootstock answers

Illustrative example — figures shown for demonstration, not live data.

Read the full technical specification →

That's what "engineered" looks like instead of "assembled" — the same standard behind all four areas above. A few questions before you sign on:

Frequently asked

Naturally, you have questions before signing on.

How is this different from hiring a software agency?

A typical agency scopes, builds remotely, and hands the system over at the end. Our engineers work inside your team throughout, and AI engagements often start from Rootstock, our accelerator, instead of a blank codebase — so there's less to hand over in the first place.

What does "plug-and-play" actually mean here?

Rootstock already has the retrieval pipeline, agent framework, and monitoring dashboard built. Your engagement is about configuring it to your documents, your domain rules, and your systems — not building those parts from scratch.

Can it run fully on our own infrastructure?

Yes — Rootstock deploys the same way to your cloud account or fully on-premise. The technical specification covers exactly what that requires.

How long before we see something working?

Typically weeks for a first working version, since the base product already exists — discovery is scoped to your domain, not to writing infrastructure.

What happens after the initial build?

A small monthly retainer keeps the system tuned as your documents, rules, and team change, so it doesn't go stale the way a one-off build often does.

Do we need an in-house AI team to maintain this?

No — that's the point of the fractional CTO and retainer model. If you later want to bring it in-house, the architecture is documented and built to hand over cleanly.