Custom automation for law firms, accounting firms, and medical offices in Pakistan and beyond.
Specialized agents designed to handle the heavy lifting of your professional practice.
Instantly reads and summarizes contracts, legal briefs, and complex documents with 99% accuracy.
Automatically categorizes, drafts, and replies to client inquiries 24/7, keeping your inbox clean.
Seamlessly collects client data, books appointments, and sends confirmations without human intervention.
We audit your firm's unique repetitive tasks and build custom agents to automate them entirely.
Book a free 15-minute call to discuss your firm's bottlenecks and goals.
We deep-dive into your repetitive tasks and identify high-impact automation opportunities.
Our team builds and integrates your custom AI agent into your existing tools in just 7 days.
Watch your productivity soar as your agents handle the boring work on autopilot.
Your data stays private and encrypted.
All client data is encrypted in transit and at rest using AES-256 encryption. Your documents and emails are never stored unprotected.
We do not store your firm's documents or client information after processing. Data is used only to complete the task and is immediately discarded.
Every client gets isolated credentials. Your workflows run on dedicated pipelines with no data shared between clients.
Our systems are designed with privacy-first principles, following international data protection standards to keep your firm compliant and your clients protected.
Flumbi is brand new — but the AI engineering behind it isn't. Here's something real I've built.
During my internship at Bank Alfalah's Premier Banking division, I built an internal LLM-backed tool that helped relationship managers quickly look up client benefit and policy information — instead of digging manually through documents and spreadsheets mid-conversation.
The tool ingested internal reference documents and let RMs ask plain-English questions to get an instant, relevant answer instead of searching for it themselves.
Personal / internship project, described here at a general, conceptual level only. No confidential Bank Alfalah data, documents, or client information is included or referenced.
The problem: RMs needed fast, accurate answers about client benefits during live conversations.
The build: a Flask backend, a document ingestion pipeline, and a Groq-hosted LLM to answer questions from that indexed knowledge.
The result: a working internal tool RMs could query directly instead of manually searching documents.
Want to be one of the first to work with us? Let's talk.
Ready to reclaim your time? Let's build your first agent.