QnA Boosted RAG with Vectara

Most web agents hallucinate. This agent is built around one rule: never ship an unverified citation. Given a start URL and a natural-language request, it fetches the page, extracts readable text, and picks the windows most likely to contain the answer using IDF-weighted term scoring instead of blindly taking the first 6000 characters. It then asks a Token Lab LLM (DeepSeek-V4-Flash) for exactly one short verbatim quote. Every quote is checked against the fetched page text; if verification fails, the agent falls back to a guarded extractive answer and records fallback_reason instead of inventing evidence. When the page truly lacks the answer, it returns an honest not-found result. Results: 11/11 evaluation questions pass, 9/9 citations verify verbatim against the source page, 0 fabricated citations, 14 pages fetched, and a multi-page demo cites the correct page. A live Token Lab run also passes 11/11 (9 LLM answers, 2 guarded extractive fallbacks). 22 unit tests pass offline. The AMD stack is load-bearing: developed on ROCm 7.2 on an AMD Instinct MI300X VF GPU (wavefront 64) with HIP kernels for vector add, histogram and reduction, rocBLAS GEMM (73x over naive), a tiled LDS transpose (14x), and rocprofv3 counter profiling. The agent itself is pure Python standard library plus the AMD Token Lab API, so it runs with one command.

PHAM MINH CANH

OpenGTM is Chronos's open-source go-to-market skills library for AI agents. It gives an agent reusable guidance for defining an ideal customer profile, researching accounts, writing cold emails, planning LinkedIn outreach and multichannel sequences, handling replies, and improving SEO and visibility in AI search. The public repository contains 17 skills in the SKILL.md format, installation options for agent tools, and a zero-dependency MCP server for loading the skills. The project separates knowledge from execution. The skills can be used for free without an account to help an agent think, plan and draft. An optional connection to the Chronos MCP provides the execution layer for contacts, messages and campaigns. OpenGTM is built by Chronos and released under the MIT License. This submission covers that public repository, not Chronos's private production code. Chronos's broader goal is an environment where companies can connect their systems, understand their data and act through coordinated agents. OpenGTM contributes a reusable GTM knowledge layer toward that goal. No AMD hardware use or completed AMD Match is claimed.

Chronos

TaskFlow is a streamlined, client-side Agile Kanban workspace engineered to eliminate friction in daily sprint tracking and hackathon task management. Modern project management software has become bloated, slow, and overly reliant on complex cloud infrastructure. TaskFlow addresses this issue by delivering an instant, distraction-free board built entirely with native web standards and local persistence. Key Features: 1. Dynamic Sprint Pipeline: Effortlessly categorize tasks across To Do, In Progress, and Completed columns with live badge counters. 2. Fluid Interaction: Full desktop drag-and-drop mechanics combined with quick-shift tap buttons for touch and mobile viewports. 3. Priority Tagging & Live Filtering: Categorize items by urgency (High, Medium, Low) and instantly filter large backlogs using the built-in search bar. 4. Zero-Latency Local Persistence: All board updates, task movements, and edits automatically serialize into browser local storage, safeguarding state across browser refreshes without requiring external logins or APIs. 5. Instant Evaluation: Ships with pre-configured sprint demo tasks so evaluators can test the complete lifecycle right away. Problem Solved: Builders and agile teams often waste critical time setting up heavy ticketing software instead of executing. TaskFlow provides a zero-setup, privacy-first management board that runs instantaneously anywhere.

NewOne

an agent that reads a natural-language request, navigates the given website (or a saved copy) and returns the one specific value asked for, with the page it came from. Not a summary, not a list of links. How it works. Each question runs as a fresh python3 /app/app.py process. A well-formed placeholder answer is written before any network access, so a crash still leaves parseable JSON. The agent fetches the start page (7 s timeouts), reduces HTML to readable text - spec tables kept as rows, menus and footnotes dropped - ranks passages with BM25 plus query coverage, and only then follows same-site links whose anchor text matches the request (max 8 pages, one hop, only when the start page held no answer). The answer comes from a type-aware extractor: price, percent, date, version, part code, e-mail, phone, number, name. The type is inferred from the question and respected strictly - a price question never returns a wattage; when no candidate of the expected type exists the answer is empty instead of a guess. Measurements keep their unit (192 + GB -> 192 GB), values lifted from the question are rejected, and a typed answer must clear a confidence floor. Output: /app/output/<query-id>_output.json with answer, citations, confidence, source_url. The Match 4 harness was not published, so the image follows the earlier Matches' container contract: mandated ROCm PyTorch base, code at /app/app.py, deps in /app/requirements.txt, no weights, no download at start-up, container alive throughout evaluation. The script accepts several argument spellings (--query/--question, --query-id/--id, --url, --corpus) plus positionals. Measured locally: 6-7 s per question over a page plus up to eight same-site pages; 0.3 s on a document corpus. Honest limits: extraction is lexical - no multi-hop reasoning; JavaScript pages are read as served HTML. Next iteration adds a resident small instruct model on the GPU to pick among candidate spans, with the deterministic pass as fallback.

Arber Arifi

A containment-first security gateway that analyzes untrusted code in an isolated gVisor sandbox and returns an evidence-based security verdict.

NomadiT