Contact Us 联系我们
Contact Us 联系我们

AI-powered
Behavioral Data
Intelligence Platform AI行为安全
与数据智能平台

Deepdata is a security platform specialized in behavioral analysis and digital interface monitoring with a data-driven approach centered on human behavior patterns. Deepdata是一个专门从事行为分析和数字界面监控的安全平台，采用以人类行为模式为中心的数据驱动方法。

Start Free Trial 开始试用
✓
✓

Our Services 我们的服务

1

Sava Lab - Security Behavior Detection & Defense 玄守 Sava Lab - 安全偏差监控与守护平台 Product

Detect risky website behavior and unauthorized access in real time with advanced behavioral analytics and defense mechanisms. 通过先进的行为分析和防御机制，实时检测危险网站行为和未授权访问。

  • Real-time anomaly detection on web visits 网站访问实时异常检测
  • DNS/HTTP log analysis with ML algorithms 基于机器学习的DNS/HTTP日志分析
  • Threat intelligence enrichment 威胁情报增强
  • User behavior baselining & risk scoring 用户行为基线建立与风险评分

Try it 立即体验
2

Narya Lab - Market Sentiment Intelligence Narya Lab - 市场情绪建模与预测实验室 Product

Advanced market sentiment analysis and predictive modeling to understand market dynamics and emotional patterns. 先进的市场情绪分析和预测建模，深入理解市场动态和情绪模式。

  • Real-time sentiment monitoring across platforms 跨平台实时情绪监控
  • Predictive market emotion modeling 预测性市场情绪建模
  • Multi-source data integration & analysis 多源数据整合与分析
  • Behavioral pattern recognition algorithms 行为模式识别算法

Try it 立即体验
3

Mira- User Behavior Insight & Journey Modeling 知界 Insight Mira Lab - 用户行为洞察与路径研究模块 Consulting

Deep user behavior analysis and journey mapping to understand digital interactions and optimize user experiences. 深度用户行为分析和路径映射，理解数字交互并优化用户体验。

  • Advanced user journey visualization 先进的用户旅程可视化
  • Behavioral pattern discovery & insights 行为模式发现与洞察
  • Predictive user behavior modeling 预测性用户行为建模
  • Cross-platform interaction analysis 跨平台交互分析

Contact US 咨询

Sava Lab - Security Behavior Detection & Defense Sava Lab - 安全行为识别与防御

AI-powered behavioral analytics and real-time threat detection with advanced machine learning algorithms and automated compliance monitoring. 基于 AI 的行为分析与实时威胁检测，结合先进的机器学习算法和自动化合规监控。

Sava Lab – AI Guard Platform Sava Lab – 智能安全守护平台

AI Engine Active AI 引擎已启动
🏠 Dashboard 🏠 仪表盘
🤖 AI Intelligence 🤖 AI 智能分析
🔍 Threat Detection 🔍 威胁检测
⚠️ Behavior Alerts ⚠️ 行为预警
👤 User Analysis 👤 用户行为分析
🛡️ ML Security 🛡️ 机器学习安全
📋 Auto Compliance 📋 自动合规监控
⚙️ AI Settings ⚙️ AI 设置
AI Behavior Analytics AI 行为分析
ML
🎯 Anomaly Detection: 96% Confidence 🎯 异常检测置信度：96%
  • Behavioral Outliers3 Detected
  • Risk ScoreHIGH
  • ML Model StatusACTIVE
Real-time Threat Intelligence 实时威胁情报
AI
Critical: 12 | High: 28 | Medium: 45 | Low: 67
Automated Compliance 自动化合规监控
AUTO
📋 GDPR Compliance: 95% Score 📋 GDPR 合规得分：95%
  • 🏥 ISO 2700187%
  • 🔐 SOC2 Type II92%
  • ⚖️ Auto Reports156
ML Security Models 机器学习安全模型
4/4
Isolation Forest • LSTM • K-Means • AutoML
AI Prediction Engine AI 预测引擎
PRED
🔮 Threat Prediction: 78% Risk 🔮 威胁预测：78% 风险
Behavioral Intelligence 行为智能分析
LIVE
🧬 New Patterns: 5 Clusters 🧬 新行为模式：5 个集群

Web Access Behavior Monitoring 网页访问行为监控

Detect risky website behavior and unauthorized access in real time with advanced behavioral analytics. 利用先进的行为分析技术，实时检测风险网站行为和未授权访问。

  • Real-time anomaly detection on web visits网页访问的实时异常检测
  • DNS/HTTP log analysis with ML algorithms基于机器学习的 DNS/HTTP 日志分析
  • Threat intelligence enrichment威胁情报增强分析
  • User behavior baselining & risk scoring用户行为基线建模与风险评分

API Usage Analytics Dashboard API 使用分析仪表盘

Comprehensive usage pattern analysis and anomaly detection across all departments and systems. 对所有部门和系统的使用模式进行全面分析和异常检测。

  • Visual trend analysis and reporting可视化趋势分析与报告
  • Department-level usage breakdown部门级使用情况细分
  • Spike and frequency outlier detection突增与频率异常检测
  • Multiple ready-to-use chart templates超百个可用图表模板

Behavioral Security Intelligence 行为安全智能分析

Aggregate logs, detect patterns, and monitor user behavior with advanced scoring and visualization. 汇总日志、检测行为模式，并通过可视化与评分监控用户行为。

  • Unified dashboard with user profiles统一仪表盘与用户画像整合
  • Dynamic risk scoring and anomaly maps动态风险评分与异常分布图
  • Enterprise integration capabilities企业系统集成能力
  • Explainable AI with human-readable alerts可解释 AI，生成可读性强的预警信息

Automated Audit & Compliance 自动化审计与合规 NEW

Continuously track risky actions, flag policy violations, and generate comprehensive audit reports automatically. 持续追踪高风险操作，标记策略违规，自动生成全面审计报告。

  • Auto-flagging of non-compliant access patterns自动标记不合规访问行为
  • Pre-built templates (GDPR, ISO27001, SOC2)内置模板（GDPR、ISO27001、SOC2）
  • Scheduled report generation and export定时报告生成与导出
  • Alert workflows for compliance teams面向合规团队的预警工作流

Narya Lab - Market Sentiment Intelligence Narya Lab - 市场情绪智能分析

AI-powered market sentiment analysis and predictive modeling across news and social media. Understand emotional market dynamics with multi-source data, behavioral insight, and real-time sentiment tracking. 通过 AI 驱动的情绪分析与预测建模，融合新闻与社交媒体数据，实时感知市场情绪动态，识别行为模式，洞察市场情感驱动机制。

Narya Lab – Real Estate Sentiment Analysis Narya Lab – 不动产情绪智能分析

🏙️ China Monitoring Active 🏙️ 正在监控中国市场
📊 Overview 📊 总览
💬 SNS Feed 💬 社交情绪
🗞️ News 🗞️ 新闻
🔮 Forecast 🔮 预测
📈 Profiles 📈 投资者画像
⚙️ Settings ⚙️ 设置
🏘️ Market Sentiment Overview 🏘️ 市场情绪概览
LIVE
Sentiment Level: Moderately Optimistic 当前情绪水平：温和乐观
🟢 Optimistic: 40% | 🟡 Neutral: 36% | 🔴 Pessimistic: 24%
💬 Real-time SNS Emotion Feed 💬 实时社交情绪流
SNS
Emotion intensity extracted from recent social activity 从社交平台提取的情绪强度
🗞️ Daily News 🗞️ 每日新闻
NEWS
  • “China REITs down amid BOJ policy uncertainty” Emotion: Fear
  • “Foreign investor demand spikes in Jing An” Emotion: Optimism
  • “Yuan volatility raises concerns for mortgage market” Emotion: Anxiety
🔮 Predicted Hot Zones 🔮 热门区域预测
FORECAST
Forecasted Investment Activity by Area 各区域预测投资热度
Based on sentiment signals and behavioral models 基于情绪信号与行为模型分析
📈 Investor Profile Breakdown 📈 投资者结构分析
DEMOGRAPHIC
Domestic Buyers: 55% | Foreign Investors: 32% | Local Speculators: 13% 本地购房者：55% | 外资买家：32% | 本地炒房者：13%
📊 Policy & Macro Signals 📊 政策与宏观信号
MACRO
"BOJ holds rates steady" → Caution rising among long-term buyers “日本央行维持利率不变” → 长线买家情绪趋于谨慎
  • KeywordsBOJ, interest rate, asset risk
  • Affected AreasShanghai Core
  • AI Risk LevelModerate

Market Emotion Forecasting 市场情绪趋势预测

Forecast future sentiment trends using time-series models trained on macro signals, news waves, and investor behavior. 结合宏观信号、新闻热度与投资者行为，利用时间序列模型预测未来市场情绪趋势。

  • LSTM & Transformer-based time-series forecasting基于 LSTM 与 Transformer 的时间序列预测
  • Daily sentiment momentum curves by asset & area按资产与区域生成日度情绪动量曲线
  • Macro-policy event alignment与宏观政策事件对齐的情绪走势
  • Volatility prediction based on emotion shifts基于情绪变化预测价格波动风险

AI Sentiment Analysis AI 情绪分析引擎

Classify, label, and score emotional tone across news, tweets, and user-generated content with large language models. 利用大语言模型对新闻、社交动态与用户内容进行情绪分类、标签提取与强度评分。

  • LLM-powered zero-shot sentiment classification基于大语言模型的零样本情绪分类
  • Entity-specific emotional tagging面向资产与区域的情绪标注
  • Fear/Greed/Uncertainty scale per sentence逐句级别的恐惧/贪婪/不确定性评分
  • Supports Multi-language analysis支持多语言情绪分析

Cross-Platform Sentiment Aggregation 多平台情绪整合引擎

Aggregate and normalize emotion signals from social media, news feeds, search trends, and forums to form a holistic view of market mood. 从社交媒体、新闻源、搜索趋势与论坛整合情绪信号，构建市场整体情绪全景。

  • Multi-source ingestion: XiaoHongshu, Douyin, Wechat, RSS多源接入：小红书，抖音，微信，新闻趋势
  • Noise filtering & duplication resolution自动去噪与信息去重处理
  • Daily sentiment index with category filters可分类过滤的每日情绪指数
  • Real-time fear & greed dashboard实时恐惧与贪婪情绪仪表盘

Investor Behavior Intelligence 投资者行为智能识别

Detect investor clusters, track behavioral anomalies, and identify early signals of trend shifts across user segments. 识别投资者群体聚类，追踪行为异常，捕捉用户行为变化中的趋势信号。

  • Clustering of institutional vs retail patterns机构与散户行为聚类分析
  • Trend-shift detection via engagement vectors基于互动向量识别趋势偏移
  • Region-based behavioral heatmaps按区域展示行为热力图
  • Emotion-movement correlation mining挖掘情绪与资金动向的关联模式