Results for “industry-intelligence”

Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions.

Systematically track competitors, analyze market moves, and produce battlecards, win/loss analysis, and positioning maps for sales, marketing, and product teams.

Mine winning ad angles, hooks, and creative patterns from top-performing ads

Pipeline Intelligence

针对某一行业（半导体、新能源、医药、消费等）的中长期基本面与产业研究，覆盖行业定义与规模、产业链与竞争格局、政策与驱动力、景气周期、趋势研判与三情景、盈利质量与落地建议。先想清楚这篇报告要证明什么判断（判断主线），再用三级数据分级取证、按固定五大板块写透，最终交付一份可直接用于战略规划、投资决策与商业化落地的飞书深度报告。对于一句话能答的问题，不要凭训练记忆或随手搜索口头作答，一律走本 Skill 的结构化多源论证。不触发并转其他场景：问该行业今天涨跌/热度/资金流/龙头股；问某个具体公司；问宏观事件对市场影响；问行业内某公司的财报。

Quantifies the business and regulatory impact of a potential data breach by inventorying sensitive data, tracing data flows, scoring exposure vectors, and estimating regulatory fines using law-sourced figures.

Automates ingestion, normalization, deduplication, and distribution of threat intelligence feeds from STIX/TAXII, open-source, and commercial sources into SIEM platforms for real-time IOC matching and alerting.

AI 原生的潜在客户情报和外联流水线。用 agent 驱动的信号评分、共同关系人排名、暖场路径发现、来源语音建模和多渠道外联（邮件、LinkedIn、X），替代 Apollo、Clay 和 ZoomInfo。在用户想找到、评估并联系高价值联系人时使用。

Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions.

Discovers key contacts across industries, roles, and social platforms via the BrowserAct API, extracting structured profile data for lead generation and outreach.

Engineering privacy and data governance: PII detection, data flow mapping, consent patterns, GDPR/CCPA-compliant implementation, DPIA. Use when privacy-by-design is needed.

Evaluates and selects Threat Intelligence Platform (TIP) products based on organizational requirements including feed integration capability, STIX/TAXII support, workflow automation, analyst interface, and total cost of ownership.

Guides privacy impact assessment for emerging technologies including IoT, blockchain, AR/VR, quantum computing, and digital twins. Covers risk identification methodology, proportionality assessment, and technology-specific privacy challenges. Activate when evaluating new technology adoption, innovation projects, or emerging tech procurement. Keywords: PIA, emerging technology, IoT, blockchain, AR/VR, quantum computing, digital twins, innovation privacy.

MLOps Engineer IA — Expert en déploiement de modèles ML (A/B testing, feature stores, MLflow, Kubeflow). Industrialise le ML du notebook à la production.

Ingests, normalizes, and enriches structured and unstructured threat intelligence feeds into STIX 2.1 format, evaluating feed quality and deduplicating indicators for distribution to SIEM, firewall, and EDR platforms.

Analyzes federal contract competitors, incumbents, and obligation trends using live USAspending.gov data via the usaspending MCP, supporting black-hat competitor research and contract-number-first obligation analysis.

Master modern business analysis with AI-powered analytics, real-time dashboards, and data-driven insights. Build comprehensive KPI frameworks, predictive models, and strategic recommendations. Use PROACTIVELY for business intelligence or strategic analysis.

Investigates insider threat indicators including data exfiltration attempts, unauthorized access patterns, policy violations, and pre-departure behaviors using SIEM analytics, DLP alerts, and HR data correlation.

Conduct internal audits against ISO/IEC 42001:2023 by identifying AIMS gaps, building an AI risk register with Annex A control mappings, and generating a 12-month Clause 9.2 audit plan.

Provides strategic and operational guidance on ITIL 4 and ITIL 5 frameworks, focusing on AI governance, sustainability, and product-centric lifecycle management.

Conduct a sector-specific threat landscape assessment by analyzing threat actor targeting patterns, common attack vectors, and industry-specific vulnerabilities to inform organizational risk management.

Monitor competitor blogs and industry publications to surface content opportunities

Prediction markets data - Polymarket, Kalshi markets, prices, positions, and trades. Use when: the user needs market data, stock analysis, watchlists, or portfolio workflows.

Generates feature ideas from PM, Designer, and Engineer perspectives for initial product discovery of a new product.

Guides the end-to-end cyber threat intelligence lifecycle from planning and direction through collection, processing, analysis, dissemination, and feedback to establish or mature a CTI program.

AI-powered financial analysis suite. Generates executive CFO briefings from QuickBooks exports (P&L, Balance Sheet, General Ledger, Cash Flow, etc.) with anomaly detection, burn rate, runway analysis, and scenario modeling. Also estimates codebase development costs with organizational overhead and AI ROI analysis. Triggers on: 'CFO briefing', 'financial analysis', 'cost briefing', 'expense review', 'runway analysis', 'burn rate', 'cost estimate', 'how much would this cost to build', 'development cost', 'Claude ROI'.

Deploys anomaly detection for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications.

Consume and produce STIX/TAXII 2.1 cyber threat intelligence feeds using Python, including server discovery, collection polling, object parsing, and SIEM/TIP integration.

Generate new feature ideas for an existing product using multi-perspective ideation from PM, Designer, and Engineer viewpoints, then prioritize the best five.

Gather competitive intelligence on companies by searching SEC filings, recent news, federal contracts, and comprehensive profiles through an MCP server.

Build industrial-grade SCADA/HMI dashboards in MATLAB following industrial-HMI conventions (ISA-101-aligned): gray-field philosophy, alarms at source, write safeguards, fixed-range trends, drill-down layout. Produces a real App Designer app (.mlapp, or plain-text .m+.xml on R2026b+) by handing serialization to the matlab-build-app skill when available, and falls back to a programmatic .m app otherwise. Use when wrapping OPC UA / Modbus / MQTT / OSI PI / PI AF monitoring scripts into a live operator app, building plant overviews, designing operator dashboards, or any time a user asks for a "SCADA dashboard", "HMI", "plant dashboard", "operator screen", or "industrial monitoring app" in MATLAB. Trigger on: SCADA, HMI, industrial dashboard, plant overview, operator screen, uigauge, uilamp, alarm banner, gray-field, ISA-101, OPC UA dashboard, setpoint, write safeguards, alarm visualization, OSIsoft PI, AVEVA PI, PI Server, PI Data Archive, PI AF, PI Asset Framework, piclient, afclient.

Implements automated PII discovery and classification using tools like Microsoft Purview, BigID, OneTrust DataDiscovery, and AWS Macie. Covers scanning schedules, accuracy tuning, false positive management, and integration patterns. Keywords: data discovery, PII scanning, Purview, BigID, Macie, OneTrust, automated classification, data cataloging.