AI agents & conversations
Turn customer conversations into useful action, with the context and controls each workflow needs.
- WhatsApp & voice agents
- Knowledge retrieval & lead qualification
- Context-aware human handoff
AI engineering & software studio
We design and build AI agents, custom platforms, and connected workflows for real business operations. Engineered end to end. Verified before it ships.
Direct founder involvement. From the first conversation to delivery.
Intent received
Send pricing to a new leadPolicy validation
Consent required before deliveryAction verified
Verified lead · policy check passedIntelligence moves things forward.
Verification keeps them on track.
Capabilities
From a focused automation to the platform around it, we build software that fits the way your business needs to run.
Turn customer conversations into useful action, with the context and controls each workflow needs.
Bring the people, information, and decisions behind your operations into a coherent system.
Connect the steps between an idea and a finished result, with clear rules for what happens next.
Selected work / 01—02
Two delivered systems, both still running. A closer look at the operational problems and the software built to solve them.
Conversation
Qualification
Human handoff
Illustrative architecture · client data excluded
An AI-powered CRM connecting customer conversations, lead qualification, partner operations, and sales visibility.
WhatsApp handles brochures, pricing, and common questions. A defined qualification flow keeps the conversation useful, with a human handoff when requested.
Voice follow-ups carry the same qualification context. The partner portal brings together identity verification, referrals, and commission tracking.
A custom dashboard covers lead sources, lead temperature, partner performance, and funnel conversion.
WhatsApp Business API · Exotel · Sarvam AI · Claude · PostgreSQL · Redis · Razorpay · Setu/DigiLocker
Production brief
AI workflow
Content output
Illustrative architecture · client data excluded
A dedicated AI content-production system built around a client's actual production requirements.
The implementation brings content work into a defined process instead of leaving it spread across individual prompts and manual steps.
Phase 1 was built and delivered as a custom content-production system. Client-identifying materials and private implementation details are not published.
Client identities and private project materials are kept confidential.
The engineering standard
A useful AI system needs more than a convincing response. Our approach connects intelligence to explicit rules, observable decisions, and the people responsible for the outcome.
Test against the tasks the system must complete and the failure cases it needs to handle.
Check the proposed action against explicit policy before it affects a customer or business record.
Make escalation paths clear and preserve the context needed to understand a decision.
Delivery approach
Each stage has a purpose. Scope, acceptance criteria, and handover requirements are agreed around your project.
Map the workflow, its users, and the points where work gets stuck.
Develop the application, integrations, and AI around the agreed process.
Challenge assumptions, test failure paths, and fix what breaks.
Put the verified workflow into use, with the operating boundaries made clear.
The studio
Satyabrata Mohanty Founder & engineer
Veyrn Labs brings product development and AI engineering together under direct founder ownership. Satyabrata has built and delivered the systems featured here, from the initial workflow to the application and integrations behind it.
Before we begin
The practical details of working together.
Projects where AI needs to work inside an actual business process: lead qualification, customer conversations, content production, CRM workflows, partner operations, and the custom software connecting them.
Yes. We start by understanding the existing workflow and the integrations it needs. API access, data quality, and platform constraints are assessed before the implementation scope is agreed.
The model proposes an action and the system validates it before execution. We use workflow-specific evaluation cases, explicit rules, and human handoff paths to define where automation can act and when it should stop.
They depend on the workflow, integrations, data readiness, and acceptance criteria. We scope those together before committing to a delivery plan or price. A focused first phase can establish the right direction before a broader build.
You work directly with Satyabrata Mohanty, the founder and engineer responsible for the systems featured here. That keeps technical decisions and project context close to the work.
The public case studies describe the delivered systems without identifying clients or exposing private data. Any additional project material can only be shared with the relevant client's permission.
Get in touch
System work in progress
Our contact system is currently being updated. For now, contact us directly by sending an email.
hello@veyrnlabs.com