Single-step automations, ordered multi-step sequences, and full graph-style workflows with branching, loops, and conditional logic, all built with a visual drag-and-drop editor.
— Case Study
AI & Machine LearningHealthcareSaaS
AI-Powered Browser Automation Platform
An enterprise client was losing hours every week to repetitive browser-based work: copying data between systems, filling out forms, and navigating multi-step workflows that only a few trained staff could remember. We built them an AI-powered browser automation platform, delivered as a browser extension, backend API, and admin dashboard, that turns any repeatable browser task into a one-click automation anyone on the team can run without writing code.
— The Challenge
The Problem We Solved
Teams were losing significant time to repetitive browser-based tasks that only a few people knew how to do correctly, with no way to record, share, or automate any of it without custom development.
Copying data between fields, filling out forms, and navigating multi-step workflows across different tools required staff to memorise exact steps with no way to record or share that knowledge.
No AI assistance existed to ground answers in the organisation's own documentation, so staff relied on tribal knowledge instead of a shared source of truth.
In clinical environments in particular, manual data entry into EHR systems was slow, error-prone, and offered no hands-free option for staff who needed one.
3
Challenges Identified
Every challenge was systematically addressed through tailored engineering and design — no workarounds, no compromises.
— Our Solution
How We Solved It
We built a full-stack browser automation platform combining a browser extension, a backend API, and an admin dashboard, giving teams a visual, drag-and-drop way to build automations without writing code.
A record mode captures a workflow simply by letting a user perform the task naturally, while a passive detection mode spots repeatable patterns in the background and suggests automations without interrupting anyone's work.
A three-layer knowledge graph (personal, system-specific, and global) powers a retrieval-augmented AI assistant that grounds every answer in the organisation's real documentation instead of guessing.
A voice-first assistant with multilingual text-to-speech gives hands-free operation on any webpage, including clinical EHR systems, with human-approval guardrails and full audit trails built in.
— Tech Stack
Technologies Used
React
TypeScript
NestJS
PostgreSQL
Prisma
LangGraph
LangChain
pgvector
ElevenLabs
React Flow
Chrome Extension (Manifest V3)
— Impact
Results & Outcomes
- 3
- Automation Complexity Tiers
- 3
- Knowledge Graph Layers
- Voice-First
- Hands-Free Operation
Any repetitive browser task becomes a one-click automation the whole team can run, so training new staff no longer means passing down tribal knowledge across a dozen different tools.
The knowledge graph gets more accurate the more the team uses it, since every interaction feeds back into the same shared system instead of staying siloed with one person.
In clinical settings, the voice-first assistant's human-approval guardrails and full audit trails give compliance teams confidence without slowing down patient intake.
Leadership gets real-time visibility into execution history, token usage, and automation performance across the whole team from a single admin dashboard.
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