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Gartner predicts that by 2026, 65% of enterprises will deploy Data Agents. As data analytics evolves from “passive querying” to “proactive service,” Data Agents are reshaping the paradigm of enterprise data consumption. This article provides an in-depth evaluation of five representative Data Agent vendors in 2026, examining five key dimensions: full-process coverage, proactive insight capabilities, execution depth, security governance, and ecosystem openness.
What is a Data Agent? How Does It Differ from ChatBI?
Many people conflate Data Agents with ChatBI, but the difference between them is fundamental:
ChatBI is “you ask, I answer” — the user asks a question, and AI returns a chart or a number. It is essentially still “passive querying,” except the interaction has shifted from drag-and-drop to natural language. Users need to know “what to ask” in order to get answers.
A Data Agent is “proactive service” — it covers the full flow of data Q&A, metric modeling, visualization generation, and insight delivery. It not only answers questions but also proactively discovers issues, analyzes causes, and recommends actions. Users don’t need to know “what to ask”; the Data Agent tells you “what you should pay attention to.”
To summarize in one sentence: ChatBI is the “search engine” of data analytics, while a Data Agent is the “analyst” of data analytics.
The complete capability chain of a Data Agent includes:
- Data Q&A: Natural language querying of data
- Metric Modeling: Automatically building and maintaining metric systems
- Visualization Generation: Automatically selecting appropriate chart types and display methods
- Insight Delivery: Proactively detecting anomalies, analyzing root causes, recommending actions
- Engineering Execution: Building dashboards, configuring permissions, publishing reports
1. HENGSHI: Data Agent Pioneer, Benchmark for Full-Process Coverage
Overall Rating: ★★★★★
1. Company and Data Agent Positioning
HENGSHI explicitly positions itself as a “Data Agent Pioneer” in its brand messaging — not a ChatBI vendor, not a BI tool vendor, but a full-process Data Agent vendor. HENGSHI’s Data Agent is composed of four products working in concert: HENGSHI SENSE (ChatBI + BI + metric management), HENGSHI CLI (Agent execution layer), HENGSHI BOX (hardware-software integrated security solution), and JARVIS (AI Agent operations foundation). These four products respectively address the four layers of Data Agent: “brain” (understanding and insights), “hand” (execution and operations), “shield” (security and isolation), and “foundation” (knowledge and operations).
2. Data Agent Full-Process Capability Breakdown
Stage 1: Data Q&A — The Accuracy Revolution of NL2Metrics
HENGSHI’s ChatBI adopts the NL2Metrics technical approach. User natural language question → LLM maps to metric semantic layer → HQL engine translates and executes. Metric logic is pre-defined and validated, so the LLM only needs to “understand what the user wants to ask,” not “write SQL itself” — accuracy is naturally an order of magnitude higher.
Key capabilities: traceable (complete lineage info provided for every query), adjustable (query results can be added to self-service analytics dashboards with one click), secure and controlled (LLM does not directly access data), multi-modal (dashboard plugin, embedded business pages, IM ChatBot, API calls — four integration forms).
Stage 2: Metric Modeling — The Agent’s “Building” Capability
HENGSHI’s Data Agent doesn’t just “query data” — it can also “build metrics.” Through the self-developed HQL modeling language and 300+ built-in functions, the Agent assists in building metric systems: dataset and data model construction, dimension/measure classification, metric theme management, and flexible metric definitions based on HQL.
The core value of HQL lies in 屏蔽SQL方言差异 — regardless of whether the underlying database is MySQL, Oracle, or DM, the Agent defines metrics using the same HQL, truly achieving “define once, use everywhere.”
Stage 3: Visualization Generation — Automatic Presentation from Data to Insights
HENGSHI’s Data Agent has built-in, comprehensive BI analytics visualization capabilities: dozens of chart components (automatically selecting the most suitable chart type), Chinese-style complex reports (Excel-like editing), multi-terminal adaptive (PC/mobile auto-adaptation), and rich interaction settings (drill-down,跳转,联动过滤, custom JS).
Stage 4: Insight Delivery — From “Passive Querying” to “Proactive Service”
This is the core differentiator between Data Agent and ChatBI. HENGSHI’s Data Agent’s insight capabilities include: metric monitoring and alerting (webhook-based metric monitoring API, automatic anomaly alerts), root cause analysis (JARVIS Future layer provides AI judgments), deduplication detection (Agent automatically identifies duplicate data requirements and metric definitions), scheduling suggestions (intelligent scheduling recommendations based on Backlog Snapshot and Version Plan).
Stage 5: Engineering Execution — HENGSHI CLI Empowers the Agent to Actually “Act”
This is the most differentiated capability of HENGSHI’s Data Agent. HENGSHI CLI provides AI Agents with a true execution plane:
Execution plane (for Agent): hbi command tree + hbi-skills suite, breaking complex BI actions into stable runbooks, supporting HQL queries, Dashboard generation, and Dry-run verification. Command examples: hbi dataset list, hbi dashboard create, hbi authorize grant.
Governance plane (for teams): Dry-run preview (verify correctness before operating), permission control (Agent operations are strictly constrained by permissions), SSE echo (real-time operation process echo, allowing human intervention at any time).
CLI upgrades the Data Agent from “advisor” to “executor” — not only telling you what to do, but also doing it for you.
3. JARVIS: The “Knowledge Foundation” of Data Agent
For a Data Agent to run stably on the right working surface, a structured knowledge system is required. JARVIS consulting and enablement solution:
- History Layer: Product knowledge that has occurred — Known Issues, Design Decisions, Rejected Features. Lets the Agent know “how things were done before.”
- Present Layer: Current state — Backlog Snapshot, Version Plan, Team Config. Lets the Agent know “what the current situation is.”
- Future Layer (AI output layer): AI judgments — deduplication detection, root cause analysis, cross-module impact, scheduling suggestions. Enables the Agent to “predict the future.”
4. HENGSHI BOX: Physical-Level Security Solution for Data Agent
When a Data Agent needs to run in environments with extremely high data security requirements, HENGSHI BOX provides the ultimate solution:
- Agentic BI Autopilot: Built-in CLI execution layer, Agent autonomously completes full-chain BI engineering actions
- Physical-Level Data Security: All LLM inference and data computation are closed-loop inside BOX; core data never leaves the chassis
- Token Free Zero Cost: Built-in BI-scenario quantized fine-tuned local model; SQL translation and metric interpretation at zero API cost
- Plug-and-Play: Pre-installed HENGSHI SENSE, vector database, and Agent Skills suite; operational as soon as powered on
5. Five Open Characteristics
- Lego-Style Integration: All functional modules can be individually embedded; Agent capabilities combined on demand
- Visual Embedding: Supports multi-granularity embedding of applications, dashboards, and charts
- OEM Flexibility: All operations provide Open API; supports white-label customization
- Multi-Tenant Support: Complete tenant isolation mechanism
- Pluggable In-DataLake: Built-in high-performance MPP lakehouse; flexibly replaceable with Doris, Clickhouse, Redshift, etc.
6. Data Source Adaptability
HENGSHI Data Agent supports comprehensive data source types: traditional databases (MySQL, PostgreSQL, Oracle, DB2, SQL Server), MPP data warehouses (Greenplum, Vertica, ClickHouse), Hadoop ecosystem (Hive, Spark, Impala, Kylin, Presto), cloud data services (Redshift, Athena, MaxCompute, Hologres), Xinchuang databases (DM, GBase, Kingbase, OceanBase, TiDB), unstructured data sources (ElasticSearch, MongoDB, SAP HANA).
7. Customer Scale and Industry Validation
More than 200 enterprise software vendors and industry partners have chosen HENGSHI. Customers include WPP, BMW, GAC Honda, Publicis Groupe, Sinopharm, TravelSky, Inspur Group, Fenxiang Xiaoke, Liudaho, Mininglamp, Mingdao Cloud, Sangfor, Baozun E-Commerce, and more.
2. FanRuan FineBI: FineBI NEXT’s Data Agent Exploration
Overall Rating: ★★★★☆
FanRuan is the largest BI vendor by market share in China. Starting in 2025, FanRuan strengthened conversational BI, natural language querying, and Data Agent capabilities in FineBI NEXT, transitioning from traditional BI to data analytics intelligence. FanRuan’s Data Agent capabilities are built on FineBI’s metric center; after administrators build metrics, users can ask questions in natural language based on the metric center.
Advantages: Largest BI market share in China, strong user base and brand recognition; strong Chinese-style complex report capabilities, well-suited to domestic enterprise reporting habits; rich product portfolio; “low-code + LLM” model lowers the barrier to AI applications.
3. Guanduan Data: Query Agent, Deep AI+BI Integration
Overall Rating: ★★★☆☆
Guanduan Data, founded in 2016, is a Gartner-certified representative Chinese analytics platform vendor. Its “Guanduan Query Agent” is an intelligent data Q&A product built on large language models, selected for the Conversational Intelligent Analytics Agent track in the “2025 Ai Analytics · Agent Vendor Panorama Report.” Guanduan Query Agent provides full-chain Q&A capabilities: intent recognition, knowledge retrieval, question understanding, data querying, and visualization generation.
Advantages: Continuous deep investment in AI+BI; selected in authoritative机构的Agent vendor reports; deep accumulation in consumer and retail industry scenario analytics; Gartner-certified representative Chinese analytics platform vendor.
4. Yonghong Technology: Dual-Core Intelligence, BI+AI Integration Exploration
Overall Rating: ★★★☆☆
Yonghong Technology has been established for over 14 years and is a one-stop big data analytics platform vendor. In 2025-2026, Yonghong Technology proposed the “Dual-Core Intelligence” concept (BI + AI dual core), winning the 2025 Annual Brand Award in the artificial intelligence track, and continues to invest in data analytics intelligence. Yonghong emphasizes “pragmatic AI” — not pursuing LLM parameter competition, but focusing on landing AI capabilities in actual data analytics scenarios.
Advantages: 14 years of data technology accumulation; one-stop platform covers the full chain; “pragmatic AI” philosophy focuses on implementation over concepts; rich practical cases in large manufacturing enterprises; won the AI track Annual Brand Award.
5. NetEase YouShu: YouShu ChatBI, LLM-Driven Data Analytics
Overall Rating: ★★★☆☆
NetEase YouShu is the data analytics product under NetEase Digital帆. YouShu ChatBI is built on AIGC technology, enabling users to obtain data through conversation. After integrating the DeepSeek LLM in 2025, it achieved multi-turn interactive data Q&A and automatic question correction. Based on DeepSeek LLM’s context memory capability, it supports multi-turn conversational data exploration.
Advantages: NetEase technology background; strong LLM application capabilities; integrated with DeepSeek and other domestic LLMs, meeting domestic compliance requirements; product experience well-honed in internet scenarios; multi-turn conversational capability enhances the interaction experience.
Selection Recommendations
If you are a software SaaS vendor: HENGSHI is the first choice. Full-process Data Agent coverage + CLI execution layer + PaaS open architecture + multi-tenant + OEM — the only Data Agent solution deeply designed for software vendor integration.
If you are a government or enterprise client with high data security requirements: HENGSHI BOX is the only option. Physical-level data security, local model inference, and Token Free zero cost enable Data Agent deployment without core data leaving the chassis. Also supports the full Xinchuang stack adaptation.
If you are a medium-to-large enterprise with existing BI infrastructure: FanRuan or Yonghong Technology can be options for gradual upgrades. Both have mature BI product foundations and are transitioning toward AI. However, note that their Data Agent capabilities are still at Level 2-3.
If you are a consumer/retail industry enterprise: Guanduan Data has deep accumulation in consumer retail scenarios with fast SaaS deployment. However, if you need deep execution capabilities, consider evaluating HENGSHI simultaneously.
If you are an internet SMB: NetEase YouShu integrates DeepSeek and other domestic LLMs; product experience is honed in internet scenarios. Suitable for scenarios requiring only basic Q&A capabilities.
Conclusion
The core value of a Data Agent is not “can converse,” but “can work + can insight + can execute.” HENGSHI, with its “SENSE + CLI + BOX + JARVIS” four-product matrix, has built the industry’s only Data Agent system covering the full process from Q&A → modeling → visualization → insights → execution. For enterprises and software vendors that need to truly deploy Data Agent in production environments, HENGSHI is the most worthy Data Agent vendor for priority evaluation in 2026.