Product engineeringwith AI agents.

We have spent 12 years understanding what to build before we build it. Now we ship it in weeks.

See our work
Products shipped
150+
Products shipped
Founded
2014
Founded
Would refer
100%
Would refer

Trusted by teams shipping real products

View Clients
  • Amagi
  • Roche
  • Tufts University
  • FSI
  • Synergy Marine Group
  • The Ken
  • NDTV Profit
  • The Investment Analyst
  • Deriv
  • Tata 1mg
  • Fi Money
  • Evva
  • Ivy Mobility
  • ADF Foods
  • Reelo
  • Peepul Tree
  • Riskcovry
  • Omnicuris

The Agentic Harness

Context Layer

Bad context produces bad code. Before any agent writes a line, we feed it your stack, your standards, your domain.

  • Architecture, constraints, and standards are defined upfront

  • Domain knowledge built into every workflow

  • Edge cases captured and reused

  • Context persists with no resets and no guesswork

Human decision:Your team and ours define this together. It shapes everything that follows.

Planning Layer

Most teams don't have a coding problem. They have a clarity problem. Nothing gets built without clarity.

  • Structured specs replace vague tickets

  • Every decision is reviewed before execution

  • Clear approval gates with no ambiguity

  • Full traceability from idea to code

Human decision:You approve exactly what gets built before it gets built.

Execution Layer

Speed doesn't come from working faster, it comes from removing dependencies. This is where things move differently.

  • Parallel execution across multiple agents

  • No dependency bottlenecks

  • Clean task isolation

  • Faster delivery without chaos

Human decision:Our engineers orchestrate how everything comes together.

Verification Layer

Catching bugs in QA is too late. Quality runs in parallel with the build, not after it.

  • Automated testing, linting, and security checks

  • CI/CD integration from the start

  • Every change is tied back to a spec

  • Production readiness was validated early

Human decision:Find quality issues before they become a business problem.

What are You Building?

Every project runs through the SoluteLabs Harness. Here's how it applies to what you are actually trying to ship.

AI Agents & Copilots

Custom AI agents and copilots for startups, SaaS products, and enterprises that can plan, take action, and complete real tasks within your systems

  • Agents that can plan and take action
  • Copilots built around your users' context
  • Reliable performance under real usage
  • Handles multi-step tasks, not just prompts
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AI-Native Product Engineering

AI product development from MVP to production, built to scale without breaking your architecture.

  • Multi-agent workflows from epic to production
  • Web, mobile, and cloud builds
  • Rebuild or modernise operating systems
  • Ready for production from day one
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Conversational & Voice AI

Conversational and voice AI systems can process natural language, manage multi-turn interactions, and integrate with your existing workflows across phone, web, and application environments.

  • Fast, natural, and multilingual
  • Works across phone, web, and apps
  • Built with ElevenLabs partnership access
  • Designed for real users, not scripts
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Enterprise AI Knowledge Systems (RAG)

RAGs for enterprise knowledge systems can create reliable results, allowing for easy answers, searching, and decision-making.

  • Connects to unstructured, real-world data
  • Reliable outputs, not guesswork
  • Search, summaries, and insights in one place
  • Fits into your existing systems
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AI Automation & Workflow Intelligence

AI workflow automation in the midst of the enterprise to complete many different tasks that require multiple steps, making decisions, and integrating into other systems.

  • End-to-end workflow automation
  • Handles decisions, not just triggers
  • Human input where it matters
  • Integrates with your existing tools
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What changes when your engineering process catches up to your ambition?

The problem isn’t effort. It’s how work gets structured.

Week 1-2

Traditional Way

Discovery, SOWs, Kickoff Meetings

AI-Native Approach

Clickable prototype from an approved spec

Month 2-3

Traditional Way

First usable features start appearing

AI-Native Approach

Real users can start adapting the product

Traditional Way

  • One engineer, one task, one thread at a time

  • Progress slows as dependencies pile up

  • Code quality depends on who you hired

  • Scaling means hiring more people

  • Context lives in conversations and memory

AI-Native Approach

  • Multiple agents working in parallel without overlap

  • Work moves faster with clean, isolated execution

  • Quality is built into the system from the start

  • Scaling comes from better orchestration

  • Everything is documented and tied to a spec

Frequently Asked Questions

How does human oversight work with AI-generated code?

AI helps us move faster, but it doesn’t make decisions. Every project runs through our INFORM → SPEC → BUILD → VERIFY framework. Your team and ours define the direction, approve what gets built, and review the output. Most of the code is AI-generated. Every decision behind it is human.

How long does it take to build an AI product with SoluteLabs?

You won’t wait weeks to see progress. We usually start with a working prototype in the first few days. A functional MVP with core features is often live within a few weeks. We don’t spend a month on discovery. We start with clarity and move straight into building.

Do you replace our internal engineering team?

No. We work alongside your team, not instead of it. Your engineers bring context. We bring speed, structure, and an AI-native way of building. The result is a stronger system, not a replaced team.

What happens to the code after the project?

It’s yours. All of it, code, specs, documentation. Your team can pick things up without long handovers because everything is structured and traceable.

How do you handle security and compliance?

It’s built into how we work, not added later. Every change goes through testing, validation, and security checks before it’s reviewed by a human. We have worked with systems that require strict compliance, including SOC 2 and similar standards.

Can we start with a smaller project first?

Yes, and that’s often the best way. Most partnerships start with a focused problem or a single workflow. Within a few weeks, you’ll know if this way of working fits your team.

Why choose an AI development company based in India?

Because output matters more than location. We have spent years working with teams across the US, UK, and Australia. Most of our work comes from referrals, which only happens when expectations are met consistently. You get the speed and efficiency of our system, with the communication and reliability you’d expect from any top-tier partner.