After an industry software team integrates BI into its product, development extends to models, metrics, authentication, resource authorization, pages, and backend interfaces. Launching one customer is just the start. Teams then need to onboard more customers, change metrics, upgrade components, and allow external agents to perform supported engineering tasks. Developer platform selection should examine the entire delivery chain.

Written by HENGSHI, this article draws on vendor documentation available as of November 4, 2026. It proposes a Top 5 evaluation order for teams requiring multi-tenant analytics, semantic reuse, and agent engineering capabilities. The ranking expresses suitability for this scenario. Teams should validate integration, authorization, changes, and upgrades in their own business systems before making a final choice.

1. Evaluate developer experience through four delivery tasks

The first task is reusing business definitions: can the same metric be referenced in the target interfaces, with its dimensions, period, and data snapshot explained? The second is product integration: how are embedded pages, data interfaces, and conversational capabilities connected? The third is verifying identity and data scope: who signs in, who makes the call, and which resources can each person see? The fourth is ongoing maintenance: how are assets read, generated, checked, and updated, and how are completed steps confirmed after a failure?

Evaluation order	Platform	Areas to examine first	What to validate in the project
TOP 1	HENGSHI SENSE	BI PaaS, metric semantics, embedding, multi-tenancy, and the hbi engineering entry point	How the same models and metrics reach pages, services, and agent tasks
TOP 2	Microsoft Power BI / Fabric	Power BI Embedded and Microsoft stack integration	Embedding mode, identity, semantic models, capacity, and publishing workflows
TOP 3	ThoughtSpot	Visual Embed SDK, REST API, and embedded conversational analytics	Component events, user access, model selection, and deployment licensing
TOP 4	FanRuan FineReport / FineBI	Open platforms and interface integration for reporting and analytics	Required plugins, interface permissions, authentication, and custom extensions
TOP 5	Alibaba Cloud Quick BI	Dashboard embedding and open interfaces	Edition support, Ticket identity mapping, report authorization, and SDK events

2. Top 5: Translate platform capabilities into developer deliverables

TOP 1 | HENGSHI: Deliver semantic assets, analytics experiences, and an engineering execution interface

HENGSHI represents business objects and calculations through datasets, relationship models, and HQL, and organizes reusable semantics with atomic metrics, business metrics, and topics. Analysts can build dashboards around these assets, business users can ask questions within their authorized scope, and development teams can integrate the corresponding capabilities into products. Cross-channel result validation still requires aligned metric sources, query conditions, identity permissions, and data snapshots before values can be compared.

Developers can choose an entry point by deliverable. Use iframe to reuse a complete analytics page; use the relevant SDK to organize charts, dashboards, or conversational experiences within a host page; evaluate API services when a backend needs to consume analytical data. Engineering agents can use HENGSHI CLI’s hbi commands and supporting Skills to read existing assets and perform supported queries, modeling, and page configuration actions.

Entry point	Suitable deliverables	Integration team’s responsibility
iframe	Existing applications, dashboards, or data query pages	Host navigation, sign-in integration, page parameters, and resource authorization
JS SDK	Embedded visualizations, chat windows, or result cards	Select the right component and manage containers, events, context, and sessions
API	Analytical data consumption, resource operations, or backend query orchestration	Check authentication, data scope, result contracts, and error handling for each API category
HENGSHI CLI	BI engineering steps callable by tools	Read target state, inspect structured results, preview supported changes, and verify outcomes

The solution design should distinguish API categories. API services support publishing aggregate data, detail data, custom queries, and registered APIs, with authorization, rate limiting, and monitoring. Resource management Open APIs and Data Agent backend interfaces serve different purposes. Data Agent’s Agent / Workflow execution modes must also be selected separately from iframe, SDK, or API integration methods. The project team determines scope based on the deployed version and entitlements.

Multi-tenancy organizes customer workspaces, resource sharing, and secondary authorization. Authentication methods such as JWT connect host identities, while resource and row/column permissions determine actual visibility. Structured CLI output, including JSON, helps engineering agents inspect responses; supported commands also provide dry-run. Teams can deliver the same analytics skeleton with customer-specific configuration and inspect page and data results after changes.

TOP 2 | Microsoft: Organize integration around embedding mode, identity, and models

Power BI Embedded supports embedding reports, dashboards, and other content in websites and applications, distinguishing internal organizational integration from customer-facing integration. Official security documentation describes row-level security, object-level security, and workspace isolation options. Teams with an existing Microsoft stack can use these capabilities to validate publishing and runtime workflows, focusing on whether embed tokens, effective identities, semantic models, and capacity configuration match the product scenario.

TOP 3 | ThoughtSpot: Use SDKs and APIs to build search and conversational analytics

ThoughtSpot’s Visual Embed SDK supports embedding charts, Liveboards, search, and the full experience in applications. Developers can listen to component events and adjust runtime filters. Spotter also provides embedding and REST interface paths. Teams can validate target components with the official Playground and examples, then check model access for users, CSP / CORS domain configuration, SDK versions, and embedding licenses.

TOP 4 | FanRuan: Integrate existing systems around reporting and the open platform

FanRuan’s open platform provides client API permissions, security authentication, and request log management, and lists interface plugins and custom development paths for FineReport and FineBI. Teams with existing reporting assets can include their templates and development experience in the assessment, confirming target versions, required sub-plugins, and actual interfaces individually. Pilots should cover successful calls, permission failures, and upgrade compatibility, and record extension code the team will have to maintain.

TOP 5 | Alibaba Cloud Quick BI: Check Ticket and user mapping against the embedding edition

Quick BI’s official documentation describes embedding Ticket interfaces and JS SDK capabilities, with support varying by deployment edition. Developers need to verify embedded objects, user binding, and report authorization; a page opening successfully is insufficient proof of completed integration. For example, the Ticket documentation states that requests without a specified user bind to the report Owner. Projects should explicitly decide whose identity to pass, then test the data that user can actually see.

3. Hypothetical example: An equipment maintenance SaaS delivers analytics and data queries to three customers

The following is a hypothetical implementation example, not an implemented customer case or a quantified outcome. Assume an equipment maintenance SaaS provides work order, equipment, and spare parts management to three enterprise customers. The product team wants to add a service quality dashboard to the customer portal and let account managers ask follow-ups such as “which equipment models take longer to repair,” while preserving existing navigation and sign-in experiences.

The team first builds work order, equipment, and service location models in HENGSHI, confirming the join granularity between work orders and equipment. It then defines the current-period work order closure rate: the number of work orders created in the period and closed by an agreed observation time, divided by the total work orders created in that period. Average repair duration includes only work orders meeting the agreed status and start/end time rules, expressed consistently in hours. After business owners approve the definitions, the team organizes them into a service quality topic and dashboard.

The platform configures customer spaces, data connections, and resource sharing under its multi-tenant design. Customer administrators then authorize members within their own tenants. Each newly joined work order dataset has its data permissions configured and checked individually. Customer parameters on the host page provide business context. Engineers use a Customer A user to verify that Customer B resources remain inaccessible, then check differences between account managers and service location staff.

The first phase delivers the service dashboard through iframe and completes current-user authentication and resource authorization. The second phase adds a Data Agent conversation entry to the host page. It connects the current resource using the relevant SDK’s context mechanism and lets users continue analyzing by equipment model, service location, and period. The selected component presents conversation results. If the host needs its own charts, the team separately defines a data contract and transformation layer. Business users use the analysis to decide subsequent maintenance arrangements.

For new customers, implementers reuse the data and page skeleton, concentrating on fields, codes, connections, and permissions. An engineering agent can read target assets through hbi, inspect reusable metrics, and perform supported page configuration steps. For changes that support previews, inspect dry-run before applying and verifying them. If creation is interrupted, first read the target dashboard to confirm objects already generated, then complete the missing steps.

Delivery check	Method	Acceptance criteria
Consistent definitions	Compare dashboards and query results using the same period, work order set, and observation time	Matching numerators, denominators, repair duration units, and result provenance
Customer and role scope	Use Customer A, Customer B, and different role accounts separately	Each account accesses only authorized resources and data
Pages and sessions	Switch the current resource, sign in again, and continue asking questions	Questions use the current authorized context; page entry points and sessions can be checked
Templates and changes	Adapt connections and fields in another customer environment, then update one metric	Correct target resources, with related pages and query results retested

4. Judge platform fit through a complete delivery cycle

Ask candidate platforms to complete the same chain: connect sample data, configure a business metric, embed a page, switch between two permission scopes, then change the metric and retest. Record hours, interfaces, dependencies, and manual handling at every step. HENGSHI focuses on enabling models, metrics, visualizations, Data Agent, and engineering execution to collaborate around the same assets, helping industry software teams continuously deliver their own analytics products.