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🤓 Latest Submissions
MobZ - Smart Router
MobZ is a hybrid token-efficient AI runtime designed to solve diverse natural language tasks while minimizing inference cost without sacrificing accuracy. Instead of sending every request directly to a large language model, MobZ introduces a lightweight cognitive pipeline that analyzes each prompt before any Fireworks API call is made. The runtime begins by loading incoming tasks from the evaluation JSON and applying a semantic prompt compression stage. Unlike traditional summarization, this component rewrites prompts into a more token-efficient representation while preserving their original intent, constraints, output format, entities, numerical values, and programming context. The compressed prompt is then processed by a custom-trained Cognitive Analyzer based on ModernBERT. Rather than generating text, this encoder performs a single forward pass to predict multiple characteristics simultaneously, including task category, estimated difficulty, reasoning depth, expected output format, and expected response length. This design provides deterministic, extremely fast inference while consuming minimal computational resources. Using this cognitive profile, MobZ consults an embedded benchmark database generated through MobZ Bench. This database stores benchmark-derived performance information for the Fireworks models available during evaluation, allowing the runtime to estimate which model offers the best trade-off between accuracy and token cost for the detected task and complexity. The routing engine then dynamically selects the most efficient allowed Fireworks model and forwards the request through the official Fireworks API. Every decision is entirely benchmark-driven and adapts automatically to the list of models provided at runtime. MobZ is fully containerized, requires no external orchestration services, and complies with the competition requirements by reading tasks from the provided JSON input, routing all remote inference through Fireworks.
13 Jul 2026
EROS - External Reality OS
EROS (External Reality Operating System) is a next-generation enterprise intelligence platform designed to help organizations understand and navigate the constantly changing external world. While companies have ERP systems for internal operations, CRM systems for customer relationships, and BI platforms for internal analytics, they lack a unified system capable of continuously monitoring, interpreting, and reasoning about external reality. Critical business signals such as competitor movements, supplier risks, market shifts, regulatory changes, pricing updates, technology adoption, and emerging opportunities already exist across the web, but they remain fragmented, unstructured, and difficult to operationalize. EROS solves this challenge by leveraging Bright Data's web intelligence infrastructure to collect, structure, and analyze public information at scale. The platform creates a living External Reality Twin for every monitored entity, including customers, prospects, vendors, suppliers, competitors, technologies, industries, and markets. Using a layered intelligence architecture, EROS transforms raw web data into evidence, evidence into signals, signals into events, and events into actionable business intelligence. The platform combines knowledge graphs, organizational memory, causal reasoning, pattern detection, and future-ready multi-agent intelligence to help organizations answer critical questions: What changed? Why did it change? How confident are we? What evidence supports this conclusion? What is likely to happen next? What action should we take? By turning the internet into a continuously updated intelligence layer, EROS enables sales teams to identify buying signals earlier, procurement teams to reduce supplier risk, security teams to detect external threats faster, and executives to make strategic decisions with real-time context. EROS transforms the web from a source of information into a system of enterprise intelligence.
31 May 2026
Sentinel BI - Business intelligence with AI
Sentinel BI is an AI-native business intelligence platform designed to transform how enterprises analyze, understand, and operationalize their data. Traditional BI tools require analysts to manually clean datasets, configure models, build dashboards, define metrics, generate reports, and explain insights. Sentinel BI reimagines this workflow by introducing a multi-agent AI architecture that automates enterprise intelligence end-to-end. Users can upload one or multiple datasets into isolated collaborative workspaces called Spaces. Once uploaded, a network of specialized AI agents activates automatically. These agents are responsible for schema understanding, embedding generation, analytics reasoning, visualization generation, governance enforcement, observability tracking, anomaly detection, forecasting, and executive report writing. The platform is powered by Gemini models through Google AI Studio and integrates AI reasoning deeply into every layer of the experience. Instead of static dashboards, Sentinel BI dynamically generates interactive analytical environments tailored to each dataset using D3.js and advanced visualization systems. The AI can identify patterns, profitability trends, churn risks, operational inefficiencies, forecasting opportunities, and correlations between business dimensions automatically. One of Sentinel BI’s core differentiators is enterprise-grade governance and observability. Every AI action is explainable, auditable, and policy-aware. The platform includes agent topology management, permission systems, explainability traces, security monitoring, and observability tooling inspired by enterprise AI governance architectures. This makes Sentinel BI suitable for organizations that require transparency, trust, and secure AI deployment.
19 May 2026
