AI systems built around how your business actually works.
We find the manual work slowing down your sales and operations teams, build the AI and automation that removes it, and connect it to the tools you already use.
The work that slows growing teams down.
Your team copies data between tools all day.
We connect your CRM, inbox, spreadsheets and internal tools so the data moves itself.New leads wait hours for a reply.
Every lead is researched, scored and routed the moment it arrives, with the follow-up drafted.Your AI pilot never reached customers.
We take it to production with testing, fallbacks and cost controls, so it holds up with real users.Nobody can see what’s actually working.
One dashboard for every workflow, lead and dollar, so decisions stop relying on guesswork.Three kinds of systems. One standard: they run in production.
AI Engineering
AI agents and features that work with real customers and real data, tested before every release.How it works →Forward-Deployed Engineering
An engineer inside your team who finds the manual work and automates it until the numbers move.How it works →GTM Engineering
Your lead data, outreach tools and CRM connected into one system, so reps spend their time on conversations.How it works →Click through the system before you pay for it.
Every engagement starts with a working demo built on sample data that mirrors your business.
Systems we’ve shipped.
The problem, what was built and the engineering behind it.
Ten studio-quality product photos in about a minute
One product photo and a few reference shots in; ten on-brand product photographs out in about a minute, checked by an automated quality gate before anyone sees them.10 images in about 60 seconds (end-to-end test, 3 of 3 runs passed)Read the case study →One platform running SEO and content for four brands, safely separated
A multi-tenant platform that pulls search and analytics data for each brand, drafts articles, scores them, sends them for review and publishes to WordPress, Shopify, Webflow or a hosted blog.199 API routes checked with 229 cross-tenant probes: 0 failuresRead the case study →3.7 million product records turned into verified, contactable leads
A pipeline that turns marketplace brand and product exports into qualified leads with a verified domain, the right decision-maker and a deliverable email, with every count reconciled back to the source.831,765 brand and 3,732,077 product records loaded and reconciledRead the case study →You see the system and the price before you commit.
It starts with a $1,500 assessment of one workflow. Credited in full against the build if you go ahead within 60 days.
Understand
1–2 weeksA fixed-fee assessment of one workflow: what it costs today and what is worth automating.Design
Before you commitA clickable demo on sample data and a fixed-price plan. You see the system before you pay for it.Build
3–8 weeksShipped into the tools you already use, in weekly working releases.Run
MonthlyWe monitor it, measure the savings against the estimate and keep improving it.The senior AI engineer you’d hire full‑time, if you could find one.
I’m Kumar Sahil. I’ve built a 15-stage generative AI product, a multi-brand content platform and a lead engine that reconciles 3.7 million records, for WorkinX, Kodify and other growing companies.
When you work with DWARY Intech, I scope your system and I write the code. No hand-offs to juniors, no account managers between you and the engineer.
Kumar Sahil
Founder & lead engineer · New Delhi, India- AI agents and LLM pipelines in production
- Lead engines, enrichment and CRM pipelines
- Workflow automation on n8n and custom Python
Find the workflow worth automating first.
Tell us about one process that costs your team hours every week. The assessment is $1,500, takes 1–2 weeks and is credited in full if you build with us. If it isn’t worth automating, we’ll say so.