Spaces:
Running
Running
File size: 2,981 Bytes
bd1ea0d a53df82 bd1ea0d a53df82 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
---
title: README
emoji: 📉
colorFrom: pink
colorTo: blue
sdk: static
pinned: false
---
# 🧠 DataArcTech
**Grounded in context graphs. Empowered by synthetic data.**
[🌐 dataarctech.com](https://www.dataarctech.com)
---
## 🚀 About Us
**DataArcTech** bridges enterprise knowledge and synthetic data to build **GenAI-ready infrastructures**.
Our core framework — **Context Graph + Synthetic Data** — enables organizations to represent, augment, and operationalize knowledge for intelligent systems.
We focus on **AI compliance, contextual reasoning**, and **data synthesis technologies** that empower enterprises to transition from static data management to adaptive, knowledge-driven AI.
---
## 🧩 What We Do
| Area | Description |
|------|--------------|
| **Context Graph (SoG / Graph Synthesis)** | A structured framework that connects data, context, and reasoning for LLM readiness. |
| **Synthetic Data Generation & Augmentation** | Produces high-quality, domain-specific datasets when real data is limited, sensitive, or unavailable. |
| **End-to-End AI Lifecycle Support** | From data synthesis and curation to model training and fine-tuning. |
| **AI Governance & Compliance** | Aligning intelligent systems with enterprise-level data governance and regulatory standards. |
---
## 🧪 Research & Open Source
We contribute to the GenAI research ecosystem through open projects and publications:
- **[ToG-2 (Think-on-Graph 2.0)](https://github.com/IDEA-FinAI/ToG-2)** – Knowledge-guided reasoning and retrieval for LLMs
- **[JudgeAgent](https://arxiv.org/html/2509.02097v3)** – An agent framework for automated evaluation of conversational and generative models
- **[SQL-R1](https://www.github-zh.com/projects/981865038-sql-r1)** – Reinforcement learning for natural language to SQL translation
- **[Awesome-FinLLMs](https://github.com/DataArcTech/Awesome-FinLLMs)** – A curated list of LLMs and datasets for financial AI research
---
## 💼 Industry Applications
Our technology powers domain adaptation and synthetic data generation in sectors such as:
- **Financial Services**
- **Manufacturing**
- **Healthcare**
- **Cloud Computing**
- **Education & Research**
We help enterprises build **domain-specialized LLMs** by combining our hybrid synthetic datasets with proprietary client data — achieving safe, contextual, and compliant AI transformation.
---
## 🌍 Our Vision
To make enterprise AI **contextually intelligent**, **data-secure**, and **governance-ready** —
where every knowledge graph and dataset contributes to a more explainable, adaptive, and trustworthy AI ecosystem.
---
## 🤝 Collaboration
We’re open to collaboration on:
- Dataset and model sharing
- LLM fine-tuning and evaluation
- Context graph / knowledge integration research
💬 Reach out via [dataarctech.com](https://www.dataarctech.com) or connect through our [GitHub organization](https://github.com/DataArcTech).
|