The startup offers an artificial intelligence platform tailored for orthopedic practices, utilizing machine learning algorithms to enhance diagnostic accuracy and treatment planning. This technology reduces the time required for patient assessments and improves clinical outcomes by providing data-driven insights.
Funding
$3.4M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Building and deploying AI applications requires significant engineering resources to manage data pipelines, integrations, and infrastructure. Developers often spend excessive time on low-level plumbing rather than focusing on core AI functionality and model optimization. Existing AI infrastructure solutions can be complex, vendor lock-in, and lack the flexibility to adapt to evolving AI technologies.
Solution
DeepStructure provides a TypeScript-native platform for building and deploying durable AI applications, enabling web developers to create self-improving AI solutions with minimal overhead. The platform offers AI infrastructure as a simple API, including managed vector stores, RAG (Retrieval-Augmented Generation), and function calling. DeepStructure's reactive event log technology handles data connectors and AI assistants, allowing developers to connect to external data sources and human interfaces without low-level data plumbing. The platform also includes a built-in feedback system to collect usage data, enabling continuous optimization of AI features.
Target Audience
DeepStructure is designed for web developers and AI engineers who want to build and deploy AI applications more efficiently, particularly those working on generative AI workloads, customer service automation, and knowledge management solutions.
Features
- TypeScript workflow platform with a blob store and Postgres provided out of the box
- AI infrastructure as a simple API, including vector stores, RAG, and function calling
- Reactive Event Log tech for managing data connectors and AI Assistants
- Pre-built connectors for data sources like Google Drive and Slack
- Built-in feedback system for collecting usage data and optimizing AI features
- Web console for monitoring application state, workflow runs, and component data flows
- Support for multiple model providers
- OpenAI Assistants API compatibility
- Option for self-hosted deployments