Openware OpenDAX™ Aurora
Aurora is a leading, modular and fully customizable exchange
Openware OpenDAX™ Aurora launched on August 30, 2023 with 2 votes. The site was still online in September 2026, 3 years on.
What it does
OpenDAX Aurora offers a modular, scalable, and white-label software, granting you full ownership of the source code for ultimate customization. Cut development time drastically and save up to 1 to 2 million dollars.
Build next-gen blockchain infrastructures and innovative Fintech projects with Openware. ✓SaaS-based ✓Request Demo
Create your own UI/UX and have full control over a highly sophisticated back-end. OpenFinex™ high-performance trading engine handles millions of trades per second. Choose from any of OpenDAX's ready built integrations with Tier 1 liquidity providers. Openware guides you through the entire end to end process and provides you with a network of a trusted third party services such as KYC/AML, Custody, Fiat On/Off Ramps, Liquidity and much more already integrated in your stack so you can get up and running FAST . Deploy your exchange software quickly and securely with OpenDAX™ Aurora, rest assured knowing you have one of the most sophisticated , battle tested , secure , and cutting edgetech…from openware.com
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Aurora – AI Gateway built in GoAug 2026 · github.com · ▲7Every Ai project needs the same infra - API keys, providers SDKs, retry logic, cost tracking. it should be infra layer. Aurora is a Go gateway that handles that layer, ~15MB binary, no dependencies. It proxies requests to OpenaAI, Anthropic, Gemini etc, and can convert between formats - use the OpenAi SDK and Aurora translates to Anthropic's wire format automatically. No format conversion code in backend. It helps: - track costs per customer/team - switch models and providers without changing code - debug requests and responses flows more easily - reduce costs with exact and semantic…


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Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…
AI · 2023 · github.com