For the work your team still does by hand: production logs, freight paperwork, job cards, or whatever yours looks like. We build agents that read, decide, and act inside your systems. And because we run three AI products of our own, you can see what we ship before you hire us.
Agents, retrieval, evals, the audit trail, and the products we run ourselves.
Three AI systems we built, shipped, and run ourselves. Open them now.
Turns unstructured company documents into a queryable knowledge brain. RAG pipelines, vector search, and grounded answers with citations.
Paste a company URL and get a full research dossier with personalized outreach drafted by AI. Built for founders doing their own sales.
Enter a target keyword and get a full SEO article with structure, internal links, and metadata. The engine behind our own content pipeline.
Four things, one standard: it runs in production, and you can prove it is right.
Not a chatbot. Agents that read the email, pull the data, update the system, and escalate what they are unsure about.
Contracts, reports and tribal knowledge, turned into something the team can ask — with citations, so answers can be checked.
Most AI projects stall on plumbing. We build the platform underneath it too — tools, dashboards, and the integrations.
Every build ships with a test set scored on your own data. Accuracy is a number you can check, not a claim we made at launch.
Most teams learn about regressions from support tickets. We build the eval harness your team runs on every change: a golden set from your traces, a judge calibrated against human labels, and a gate in CI.
A fixed-scope, 2–3 week AI agent evaluation: a failure taxonomy from your traces, a 150–300 case golden set, an LLM judge calibrated against human labels, and a regression gate in CI.
What it coversMove to a newer or cheaper LLM without regressions: side-by-side quality, cost and latency scores on your own traffic, routing and caching, and a cutover with rollback in 2–3 weeks.
What it coversFor the workflow your team still does by hand. Nobody should commit to a build before seeing the thing work on their own documents.
Fixed scope, agreed before kickoff. The pilot is credited in full toward the build.
Scope and fee fixed in writing before the build starts, against the pilot or audit evidence.
Monthly. Scope set by volume, number of agents, and the response time you need.
“Rottawhite didn't just write code. They redesigned how our operations work. The AI workflow they built eliminated 60% of our manual processing overnight. It felt less like hiring a vendor and more like adding a co-founder.”
The short version
Rottawhite is an AI engineering studio in Bengaluru, India that builds production-grade AI agents and RAG systems, and evaluates the ones already running. AI teams start with an Agent Reliability Audit; operations teams start with a two-week Workflow Pilot on their own documents. ELISRUN cut defects 60% and lifted production 40% with a Rottawhite-built system.
Ready to build?
Tell us what you need. Fill out the form and a senior architect will get back to you within 24 hours.