🤝 Top Collaborators
🤓 Latest Submissions
Maestro — Governed Multi-Agent Incident Response
Maestro: Governed Multi-Agent Incident Response Enterprise incident response is a high-stakes, collaborative environment where coordination failure is the primary risk during a breach or outage. Maestro transforms this chaotic process into a governed multi-agent system where Band serves as the primary coordination layer. Every incident triggers a dedicated Band room where a squad of 11 specialized agents—including Intake, Correlation, and Mitigation specialists—collaborate in real-time. Unlike standalone AI tools, Maestro agents hand off context through structured messaging and post findings live in a shared chat alongside a human commander. The system is engineered for regulated workflows. For critical SEV-1 and SEV-2 incidents, Maestro enforces a structural Human-in-the-Loop gate. Irreversible actions are blocked until the human commander provides explicit approval directly within the Band interface. This "Safety-by-Default" approach ensures that no AI can autonomously execute high-impact changes without human accountability. To meet strict compliance standards like SOC2, HIPAA, and DORA, every interaction is mirrored to a tamper-evident audit trail protected by SHA-256 hash chaining. By integrating four diverse AI frameworks—Claude, Gemini, GPT-4o, and Llama 3—Maestro offers cross-provider resilience, ensuring the response pipeline remains active even if a specific provider faces rate-limits. Maestro turns manual coordination into a provable, safe, and automated workflow.
19 Jun 2026
RevenueRadar
RevenueRadarAI is an autonomous deep-web intelligence engine designed to give Go-To-Market (GTM), sales, and product teams real-time visibility into competitor movements before they impact revenue. The platform solves the biggest challenge in market intelligence: stale, geo-blocked, and unstructured data. Using Bright Data’s full infrastructure stack, the application automatically maps the competitive landscape. At signup, the platform utilizes the SERP API to perform multi-angle competitor searches. Every 5 minutes, an autonomous background monitor tracks competitor updates. The system uses Web Unlocker to retrieve pricing pages and Scraping Browser to parse JavaScript-heavy pages like LinkedIn and Crunchbase via the MCP Web Scraper API, storing social sentiment from Reddit and competitor funding updates. To compile these raw web signals into strategic assets, the application feeds data into an AIML API reasoning loop (using GPT-4o-mini) to generate competitor battlecards, win/loss playbooks, and calculate B2B account buying intent scores (0-100) based on real-time hiring trends. Furthermore, the platform integrates Speechmatics to transcribe competitor podcasts and product keynotes, and uses Cognee's graph memory sidecar to build a semantic database of market signals across sessions. Critical alerts are pushed instantly to sales teams via Slack webhook integration.
31 May 2026
MarketMaster AI
The Problem Small and medium enterprises (SMEs) in emerging markets manage over 70% of their operations using physical paperwork, manual ledgers, and fragmented supply chains. This reliance on analog processes leads to severe stockouts, customer churn, and a complete lack of forecasting, causing SMEs to leak up to 30% of their potential annual revenue. Legacy ERP systems fail here because they demand high digital literacy, steep upfront costs, and manual data entry that traditional store owners cannot sustain. The Solution: MarketMaster AI MarketMaster AI is an autonomous, multi-agent B2B retail digitization and automation platform that bridges this analog-to-digital divide. Powered natively by IBM WatsonX Granite (Granite-3-8b-Instruct and Granite-3-2b-Vision) and developed with the assistance of IBM Bob, the platform features four specialized AI agents operating in an autonomous ReAct tool-calling loop: IBM Bob Agent (Vision-to-Code & NL2SQL): Users take a photo of a physical delivery challan or invoice. The agent extracts structured data, updates the database via secure SQL mutations, and enables natural language querying (NL2SQL) in English or Urdu. Stock Sentinel Agent: Predicts stockouts based on sales velocity and automatically drafts optimized purchase orders. Sales Scout Agent: Monitors customer purchase patterns to detect early signs of buyer churn and flags attrition risks. Market Agent: Provides competitive external intelligence and localized pricing optimization strategies. Technical Implementation & Value Built on React 19, TypeScript, and Express, the platform replaces manual logs with automated webhooks and n8n background workflows. Security. By targeting the 40 million retail and wholesale SMEs in emerging markets, MarketMaster AI cuts administrative overhead by 60%, eliminates human error, and recaptures lost sales through immediate inventory replenishment and autonomous customer re-engagement.
17 May 2026
