Talks

Speaking engagements and public presentations from Smaht.ai members

DocRouter Flows: Visual Workflow Automation for Intelligent Document Processing

DocRouter Flows: Visual Workflow Automation for Intelligent Document Processing

Andrei Radulescu-Banu
Most document AI tools give you one-step LLM processing. The second a customer needs branching, agents, or human-in-the-loop, you need more. DocRouter Flows is a visual, document-native workflow system with first-class OCR/LLM nodes, sandboxed Python, and durable execution via node-level checkpoints—no Temporal cluster required. Lightweight to run, and in production at scale.
How AI Agent Memory Works

How AI Agent Memory Works

Andrei Radulescu-Banu
How to design AI agent memory and how it behaves in production: extracting memory facts from the incoming prompt, deduplicating and reconciling them with existing entries in AWS Aurora pgvector, injecting prior facts into LLM context, and scalability/optimization strategies for selecting only the most relevant facts. Covered implementation with Mem0 and custom save & retrieve LLM prompts—now a standard capability across ChatGPT, Claude, Grok, and Gemini.
How To Embed an AI Copilot in Your Application

How To Embed an AI Copilot in Your Application

Andrei Radulescu-Banu
How we embedded an AI copilot into DocRouter as a tool-calling Document Agent: the agent loop, tool approval UX, context injection, and the backend patterns that make agents reliable in production.
The 'One Codebase, Many Products' Playbook

The 'One Codebase, Many Products' Playbook

Andrei Radulescu-Banu
Shared our journey with The 'One Codebase, Many Products' Playbook at AnalytiqHub.com, turning one framework into a powerhouse for AI products. From building DocRouter.AI in 3 months to launching SigAgent.AI in 3 weeks, and customized AI portals for clients – it's all about slashing dev time with 90%+ reuse. Core Playbook Steps: Build Shared Foundations (React UI, FastAPI backend, MongoDB storage, and Claude Agent for workflows), Integrate Smartly (LiteLLM for LLMs and Stripe for seamless billing), and Scale with Ease (open-core for community, closed forks for clients).
SigAgent.AI - Tracing Claude Agents

SigAgent.AI - Tracing Claude Agents

Andrei Radulescu-Banu
AI agents have become powerful and reliable, but you need to build them right. With 50% of new agents now built with Claude Code, the ecosystem has opened up for integration with MCP, marketplaces, plugins, and SKILLS.md. What's missing? AI Agent Evaluation for debugging during development, and for guardrails and monetization during deployment. SigAgent.AI specializes in tracing Claude agents using Open Telemetry and step-by-step, hook-level monitoring. We covered how to build Claude Agents with SigAgent.AI traceability, what works and what doesn't with MCP tools, CLAUDE.md, SKILLS.md and MCP-as-code, and how to stand up agent infrastructure for value-based and usage-based pricing.
How To Integrate Stripe Into Your AI Application

How To Integrate Stripe Into Your AI Application

Andrei Radulescu-Banu
How did we built Stripe billing into DocRouter.AI? The talk covered why Stripe was the right choice for scaling metered AI usage, our SPU (Service Processing Units) credit system inspired by Databricks DBUs, free tier → plans → a-la-carte credits with consumption waterfall, dynamic pricing config 100% in Stripe metadata, async Stripe API calls in FastAPI, and our MongoDB backend schema.
How To Train Your AI Agent

How To Train Your AI Agent

Andrei Radulescu-Banu
What are the steps to create an AI Agent? Our AI Camp talk is a deep-dive into how AI Agents are implemented, in practice. With lessons learned from our DocRouter.AI coding agent, and our consulting engagement implementing a coding agent for lab information management systems company Starlims.
Engineering with Guardrails: Innovating in Regulated Spaces

Engineering with Guardrails: Innovating in Regulated Spaces

Ilsa Webeck, Andrei Radulescu-Banu, Marjan Monfared
Building fast doesn’t mean ignoring the rules—especially in healthcare, fintech, AI, or consumer hardware. Our panel explores how to embed compliance into the development process without slowing innovation - for CTOs, technical founders, and engineering leaders operating in regulated industries. Moderated by Rabeeh Majidi.
GradeAssist AI: A School Quiz Grader

GradeAssist AI: A School Quiz Grader

Andrei Radulescu-Banu
GradeAssist is a new tool for teachers, using AI to grade open-form school quizzes, with teacher-in-the-loop – using DocRouter as an AI middleware, with a new front-end UI generated by Bolt AI.
An AI Backbone for Document Processing
Mindstone Boston
Mindstone Boston logo

An AI Backbone for Document Processing

Andrei Radulescu-Banu
At the Sundai MIT hackathon, we recently develop a flow that grades 5th grade quizzes against a configured rubric. DocRouter.AI implements the back end, with the teacher-in-the-loop able to correct the evaluations. We reviewed this hack!

A front-end UI specialized for this use case can be quickly developed with tools like Manus, Bolt AI, Cursor, Windsurf. The DocRouter is the a tech stack accelerator, just managing prompts and evaluations, with human-in-the loop, hiding the complexity of LLM workflows.
AI Document Workflows
AI Tinkerers & CarGURUS
AI Tinkerers & CarGURUS logo AI Tinkerers & CarGURUS logo

AI Document Workflows

Andrei Radulescu-Banu
DocRouter.AI is a drag-and-drop UI that transforms unstructured docs into ERP data – integrated with MCP clients like Claude Desktop – building web dashboards, dynamically – for example, allowing consulting companies to optimize internal engineering resources allocated to contracted projects.
Smart Document Router
PyData Boston & MODERNA
PyData Boston & MODERNA logo PyData Boston & MODERNA logo

Smart Document Router

Andrei Radulescu-Banu
The DocRouter.AI is an open source Document Understanding Tool. It performs data extraction, at scale, for intelligent automation in a number of verticals: Supply Chain, Healthcare, Finance.

It is implemented using:
– NextJS, NextAuth, TailwindCSS
– FastAPI, Pydantic
– AWS, MongoDB
– LiteLLM
– OpenAI, Anthropic, Gemini, Groq/DeepSeek

To Andrei's surprise, the Cursor AI editor wrote most of the DocRouter.AI code! We discussed how DocRouter.AI was coded.
AI Human-in-the-Loop Panel
AI Furnace & Aethos

AI Human-in-the-Loop Panel

Andrei Radulescu-Banu, Dipali Trivedi, Brian Benedict
Panel discussion on how human-in-the-loop is implemented in practice, when used during LLM development vs in end products, LLM model evaluation, and the importance of humans understanding AI-generated code. Moderated by Nico van Wijk.
LLM Orchestration At Scale

LLM Orchestration At Scale

Andrei Radulescu-Banu
Why do we need to orchestrate Large Language Models (LLMs)? We will talk about Perplexity.AI's approach, shared openly in their podcasts – and at enterprise workflow automation with unstructured data at scale.
How To Build A Self-Driving Car – A Look at Robotics System Design

How To Build A Self-Driving Car – A Look at Robotics System Design

Andrei Radulescu-Banu
Sensors, control, planner, perception, mapping – how is a self-driving car built? An introduction for general engineering audiences, zeroing in on the integration of ROS (Robot Operating System) and system design principles in constructing autonomous vehicles.
Using LLMs and NLP for Digital Health Automation

Using LLMs and NLP for Digital Health Automation

Andrei Radulescu-Banu
Review of Large Language Models (LLMs) and Natural Language Processing (NLP) applications for business process automation in digital health: Nurse doing pre-op patient screening; and Insurance Claims Processing Automation