Top Builders

Explore the top contributors showcasing the highest number of app submissions within our community.

Chroma

Chroma is building the database that learns. It is an open-source AI-native embedding database. Chroma makes it easy to build LLM apps by making knowledge, facts, and skills pluggable for LLMs. The fastest way to build Python or JavaScript LLM apps with memory

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Relese date2023
AuthorChroma
Typeembedding database

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Chroma AI technology page Hackathon projects

Discover innovative solutions crafted with Chroma AI technology page, developed by our community members during our engaging hackathons.

NexusOps – Autonomous Industrial Maintenance

NexusOps – Autonomous Industrial Maintenance

NexusOps is an autonomous industrial maintenance platform that helps manufacturing teams reduce machine downtime through intelligent multi-agent orchestration. Modern industrial environments generate vast amounts of operational data, yet diagnosing failures, identifying root causes, checking spare part availability, and preparing maintenance procedures often remain manual, time-consuming processes. These delays lead to increased operational costs, production losses, and extended equipment downtime. NexusOps addresses these challenges by coordinating specialized AI agents that collaborate throughout the maintenance lifecycle. When an operator reports an incident, a triage agent evaluates the issue and initiates the appropriate workflow. A telemetry agent analyzes machine sensor data to detect anomalies, while a diagnostics agent combines real-time telemetry with Retrieval-Augmented Generation (RAG) to retrieve relevant maintenance manuals, SOPs, and historical troubleshooting knowledge, enabling accurate root-cause analysis. An inventory agent verifies the availability of required replacement parts before maintenance begins, ensuring engineers can execute repairs without unexpected delays. A supervisor agent consolidates the outputs from all agents, generates a detailed maintenance plan with repair procedures, safety recommendations, required tools, estimated repair time, and confidence scores, then routes the plan for mandatory human approval before execution.

Precision Onco Africa

Precision Onco Africa

**The problem.** Half of all human cancers carry a TP53 mutation. In low-specialist- density regions, there is often no oncologist and no geneticist to interpret it — and no reliable internet to look it up. Clinicians face refer-and-wait or guess. What we built.- Precision Onco Africa convenes the multidisciplinary tumour board the frontline lacks. Six specialist personas;- pathologist, geneticist, oncologist, surgeon, pharmacologist, and an equity officer — reason over the case. Each returns a probability distribution over the options; we graph the consensus and the disagreement. A dedicated adversarial-skeptic agent hunts for contradicting evidence, ClinVar/IARC guardrails flag uncertainty, and the tool is research-use-only by design. It never claims to diagnose. Creative use of Gemma 4- a multimodal reasoning core, not a chatbot. Gemma sees a rendered p53 structure and reasons about the mutation's warp; reads photographed lab reports and H&E slides with no OCR layer; *casts a mathematical vote* as one of six personas; *argues against itself*; and *speaks Kiswahili* for the patient-facing report. Five distinct jobs from one model. **Use of AMD.** A single `INFERENCE_MODE` switch makes the platform hardware-elastic: serialized and quantized on a commodity 8 GB laptop (fully offline), or parallel- batched on **AMD Instinct GPUs via Fireworks/vLLM** — no code change. Moving inference to AMD Instinct cut answer latency from **182 s to 5.1 s (~35×)**, the difference between the tumour board being unusable and feeling real-time. A ROCm/vLLM benchmark harness and an autonomic self-healing GPU-ops layer read **real** `rocm-smi`/`psutil` telemetry — we never fabricate hardware numbers. Completeness- 26 agents, real evaluation against ClinVar/IARC ground truth, containerized and deployed live. Built solo, on an 8 GB laptop. Why it matters-Precision oncology that scales from the Cloud to the Clinic on the same codebase — built for the places the internet forgets.

Adaptive Cost-aware LLM router

Adaptive Cost-aware LLM router

RouteZero is a hybrid token-efficient AI routing agent built for the AMD Developer Hackathon ACT-II Track 1. It solves the core enterprise AI problem of minimizing remote API token costs without sacrificing answer quality. Every incoming prompt is processed through a multi-stage pipeline: first hitting a ChromaDB semantic memory cache (cosine similarity ≥0.92) for zero-token responses on repeated queries, then passing through a custom Semantic Heuristic Router that classifies prompts across 8 capability domains using sentence-transformer embeddings and weighted heuristic signals. Simple tasks (factual knowledge, math, sentiment, summarization, NER) are handled locally by a Qwen2.5-1.5B 4-bit quantized GGUF model running on CPU at zero Fireworks token cost. Complex tasks (code generation, debugging, logical reasoning) are escalated to a frontier model via Fireworks AI. A deterministic verification layer catches low-quality local responses and triggers automatic fallback to remote inference. The entire pipeline is orchestrated via LangGraph state machine, containerized for linux/amd64, and optimized for the 4GB RAM / 2 vCPU grading environment. RouteZero demonstrates that intelligent routing — not raw compute — is the key to scalable, cost-efficient AI in production.

NyayaMitra — AI Legal Aid Agent

NyayaMitra — AI Legal Aid Agent

500 million Indians cannot afford a lawyer. When a landlord cheats you, when your employer withholds wages, when a defective product harms you — most citizens have no idea what their legal rights are. Legal aid is expensive, inaccessible, and delivered in English that most people don't understand. NyayaMitra changes that. NyayaMitra is a Retrieval-Augmented Generation (RAG) powered legal aid agent built on Gemma 4 31B via Google AI Studio. It ingests three foundational Indian legal statutes — Transfer of Property Act 1882, Consumer Protection Act 2019, and Code on Wages 2019 — chunked into 566 segments and stored in ChromaDB. When a user asks a question, LangChain retrieves the most relevant legal sections and passes them to Gemma 4 31B, which generates grounded, cited answers — not hallucinations. The Gradio interface offers three features: (1) Document Analyzer — upload any contract or agreement and get plain-language clause analysis with risk flags; (2) Ask Your Rights — ask any legal question and receive answers citing actual Indian law sections; (3) Draft a Letter — describe your dispute and receive a formal legal notice ready to send. Gemma 4 31B was chosen specifically for its long-context window and instruction-following capability, which are essential for parsing dense legal text and generating structured legal responses. The entire pipeline runs in Google Colab with zero local setup required, making it accessible to developers and citizens alike. NyayaMitra targets both the Unicorn Track and the Gemma 4 Bonus Challenge. The project is open source under MIT license and built solo in under 48 hours.

AITinerary

AITinerary

AITinerary – Your AI Travel Co-Pilot AITinerary is an AI-powered travel planning platform designed to simplify every stage of a trip—from discovering destinations to creating personalized itineraries and exploring hidden gems. Instead of spending hours researching across multiple websites, users simply describe their travel preferences, budget, trip duration, and interests, and AITinerary generates a complete travel plan tailored to them. One of the core ideas behind AITinerary is bridging the gap between travel inspiration and actual trip planning. Today, many people discover amazing destinations, restaurants, and experiences through Instagram Reels and YouTube videos, but planning a trip around that content is still a manual process. AITinerary aims to let users provide a Reel or YouTube link and transform that inspiration into a practical itinerary with recommended attractions, restaurants, accommodations, transportation, and nearby experiences. The platform also acts as an intelligent travel companion throughout the journey. It recommends hidden gems beyond popular tourist attractions not to miss, adapts plans based on user preferences, provides contextual information about places, helps optimize travel budgets, and enables expense tracking and bill splitting for groups. For the MVP, the focus is on AI-generated itineraries, social media-inspired trip planning, personalized recommendations, and intelligent travel assistance. The architecture is designed to integrate with travel providers and booking platforms in the future, allowing users to seamlessly transition from planning to booking within a single experience all at one place. By combining generative AI, travel data, and personalization, AITinerary aims to become an all-in-one travel assistant that helps users spend less time planning and more time experiencing memorable journeys. "From inspiration to itinerary in seconds. See it. Plan it. Experience it."

Esillio: The operating system for human biology

Esillio: The operating system for human biology

Healthcare is deeply fragmented—every consultation starts from scratch, and patient history is scattered across isolated PDFs. Esillio solves this by serving as a longitudinal intelligence layer that continuously compiles your biological history into a structured, privacy-preserving timeline. Our architecture leverages AMD's advanced compute ecosystem in a highly strategic way. Rather than requiring users to have massive local GPUs, we use AMD Instinct™ accelerators and ROCm to power our proprietary Biological Continuity Compiler™. This pipeline distils the massive Gemma 4 foundational model down into a highly optimized 17MB micro-artefact. This tiny compiled model is natively embedded directly inside our Docker container, allowing it to run completely offline on standard consumer CPUs with zero cloud dependency. This AMD-powered approach forms our strategic moat. By solving the "cold start" problem of fragmented health history locally and privately, we build a high-retention, patient-owned data ecosystem. This highly defensible intelligence layer becomes the ultimate integration point for wearable manufacturers, digital therapeutics, and telemedicine platforms. By utilizing AMD's enterprise hardware to generate deployable edge intelligence, Esillio OS achieves instantaneous clinical reasoning while building the privacy-first foundation for the modern health economy. Your body remembers everything—it’s time healthcare did too. Esillio is here to cure the amnesia of modern medicine. Stop treating your health like a Snapchat story.