Udit Akhouri

Referral Growth Engine

The Problem: Healthcare organizations rely on highly fragmented public records, manual spreadsheet tracking, and static CRM workflows to map clinical referral networks and identify growth opportunities.

The System: An autonomous go-to-market orchestration platform built at Emora Health. The architecture operates continuously in the background, executing multi-agent retrieval and entity resolution across public healthcare datasets to manage physician discovery, behavioral profiling, and geo-spatial lead mapping.

The Outcome: Replaces manual research and data entry with continuous business development intelligence, enabling growth teams to act on verified, prioritized provider networks with zero operational overhead.

Referral Insight

The Problem: Evaluating a single physician or clinical practice for business development requires parsing unstructured data across dozens of public registries, academic publications, and organizational hierarchies.

The System: A highly precise data enrichment engine built at Emora Health. The system ingests a raw physician name and orchestrates parallel retrieval pipelines across the NPI Registry, NPPES, provider affiliation databases, and practice histories.

The Outcome: Combines complex entity resolution with automated reasoning to synthesize a structured, instantly actionable intelligence profile for go-to-market execution.

Brane

An AI-native governance and compliance infrastructure designed to verify the operational reliability of large language models in high-stakes healthcare environments. Rather than treating safety as an alignment afterthought, Brane establishes deterministic guardrails and continuous behavioral evaluation pipelines to ensure clinical AI systems execute reliably within bounded operational parameters.

SuperDocs

An intelligent developer platform that embeds living technical documentation directly into automated retrieval pipelines. Built to solve the synchronization gap between complex codebases and developer awareness, the architecture provides a persistent structural memory utilized by over 500 developers.

ADHD for Agents

An exploration into non-linear, parallel divergent thinking architectures for large language models. Rather than constraining an agent to a singular chain-of-thought, the system forks execution paths across multiple concurrent reasoning threads before evaluating and converging on an optimal solution. The architecture demonstrated an approximate 4× improvement on complex reasoning benchmarks, achieving over 880 GitHub stars and extensive adoption across the open-source AI research community.

Reasoning Systems & Open-Source Infrastructure

Active research investigations focusing on multi-agent orchestration, structural workflow synthesis (Brainrail), and reverse-engineering proprietary agent runtimes to establish open-weights model support (Brane Code). These projects serve as experimental testbeds for testing the boundaries of autonomous execution and future agent runtimes.