AskTuringAI vs Gadeon

AI That Actually Knows Your Business Stop getting generic AI responses that miss the mark. AskTuring delivers accurate, verifiable answers grounded in your company’s actual documents, policies, and knowledge—without the hallucinations and guesswork of typical AI tools. What You Get With AskTuring 90% Faster Information Access * Find answers in seconds instead of hours searching through documents * Access 100% of relevant information vs. 30% with traditional keyword search * AI automatically surfaces the exact information you need Answers You Can Trust * Every response is backed by your actual documents with exact page-level citations * Click any citation to instantly verify the source * On-demand confidence scoring validates critical information across multiple AI models * Ideal for compliance, audits, and high-stakes decisions Complete Data Security and Privacy * Your data never trains external AI models * Anonymous queries protect your organization’s identity * Enterprise-grade encryption with SOC 2 compliance * Role-based access controls keep sensitive information secure Flexible and Future-Proof * Choose from GPT, Claude, Gemini, or let AI automatically select the best model * Optional real-time web search for current information * Adapts to new AI models without migration * Improves continuously based on user feedback Why Companies Choose AskTuring Instead of Generic AI * Hallucinated or made-up information * No way to verify sources * Generic responses without business context * Data used to train public models With AskTuring * Accurate answers from your own documents * Click-to-verify source citations * Context-aware responses tailored to your business * Complete data privacy and control

Gadeon runs Qwen3.5 and QwenPaw hybrid language models entirely on your device's Apple Neural Engine, using Core ML as its only framework dependency. There's no C, no Python, and no cloud calls: every token is generated locally, keeping your conversations private. Under the hood, these models mix Gated DeltaNet recurrent layers with a smaller number of attention layers. Gadeon compiles that hybrid architecture directly onto the Neural Engine's dataflow accelerator, so both prompt processing (prefill) and token generation (decode) run on-chip instead of falling back to the CPU or GPU. On an Apple Silicon Mac, prefill measures roughly 2 to 2.4 times faster and about 4.4 times more energy-efficient per token than a Metal GPU baseline, while leaving the GPU free for other work. Conversations in Gadeon are append-only: each turn extends the model's fixed-size recurrent state instead of re-processing the entire chat history, so response latency doesn't grow as a conversation gets longer. The app can also roll back to an earlier point in a conversation, dropping reasoning traces or replaying tool calls in a clean form without reprocessing everything from scratch. For ternary-quantized models, Gadeon switches to a pure-Swift Metal GPU backend behind the same session and tokenizer interface, so both compute paths feel identical from the chat UI. Gadeon is a proof of concept for bringing Gated DeltaNet hybrid models to the Neural Engine through Core ML - built to explore what's possible on Apple's own silicon.