DATA+AI Strategy Launched: Sinovatio Makes AI Truly Take Root at the Business Frontline and Create Value

The wave of large models is sweeping across the digital industry, and artificial intelligence has become the core engine of enterprise transformation and upgrading. Yet beneath the surface, "hard to deploy, costly to invest, slow to show results" has become a common dilemma facing countless enterprises: investing heavily to build systems and procure software and hardware, only to end up with "systems that cannot be built, technology that cannot be put to use, and value that cannot be realized." While the industry drifts into an internal race of "prioritizing top-level design over frontline implementation," finding an AI transformation path that fits the real operating conditions of enterprises — low-cost, highly flexible, and iterable — has become the question the whole industry urgently needs to answer.

On June 4 in Suzhou and June 17 in Nanjing, Sinovatio appeared successively at Lanling Intelligence's 2026 AI Product Experience events, unveiling its DATA+AI core strategy comprehensively and systematically for the first time. Breaking from conventional industry thinking, Sinovatio abandoned the "asset-heavy, long-cycle" mode of whole-domain restructuring, adopting "knowledge distillation" as its methodology, "AI Digital Twin" as its tool, and "on-site delivery" as its closed loop. The goal is clear: to forge a differentiated path of "pragmatism first, value first," providing enterprises with a deployable, replicable, and scalable new solution for AI transformation.

Rooted in the real pain points of countless enterprises, Sinovatio chose the pragmatic route of "knowledge-based AI Digital Twin," overturning traditional construction logic. We no longer insist on "governing all data first, then building AI applications." Instead, we place job knowledge and business skills at the core, returning to a highly flexible knowledge dimension, bypassing lengthy whole-domain data governance, and letting AI reach the business frontline directly — deploy first, then iterate; validate value first, then scale up.

AI ApplicationFactory: Building the Core Capability Foundation

A pragmatic deployment path depends on a strong technical foundation. Sinovatio's DATA+AI strategy is built on AI ApplicationFactory as its capability foundation, driven by two engines — the DI Data Engine and the AI Intelligence Engine — breaking down the barriers between structured data and unstructured knowledge, and turning enterprises' dormant data assets into productivity that drives business growth.

DI Data Engine: Revitalizing Structured Data and Mapping the Full Business Data Landscape

ERP, MES, CRM, PLM, WMS, HR — dozens of systems each running independently, with scattered data, inconsistent standards, and broken relationships, is the reality for most enterprises. The DI Data Engine takes a pragmatic approach: business-oriented, breaking down system barriers, and linking scattered data along real business processes. The platform handles the full workflow — business domain mapping, entity relationship construction, data standard definition, data quality control, data security classification, and responsibility matrix implementation — building a clear, visible business data map. Obscure and fragmented business data becomes systematized, standardized, traceable, and callable, so data assets are truly "visible, manageable, and usable."

AI Intelligence Engine: Awakening Enterprises' Sleeping Knowledge Treasures

Documents, drawings, reports, audio and video, contracts, technical manuals — these unstructured materials account for a large share of an enterprise's information assets, yet they have long lain dormant. The AI Intelligence Engine is purpose-built for this, supporting multi-channel access from local, FTP, and collaboration platforms, and compatible with all formats including text, tables, images, audio, and video. Through intelligent document parsing, content chunking, AI tag generation, semantic association, and fine-grained permission management, the platform distills fragmented materials into standardized knowledge and builds an enterprise-specific knowledge base; backed by RAG indexing and semantic metadata graphs, unstructured knowledge truly begins to flow and becomes callable by AI.

Deep Integration of the Two Engines: Tackling Multimodal Data Invocation

The DI Data Engine produces business metadata, while the AI Intelligence Engine accumulates semantic metadata; the two engines are deeply linked through a unified metadata graph. An AI Digital Twin can use a single query logic to retrieve both structured business data and unstructured knowledge-base content, overcoming the industry challenge of unified multimodal data invocation. This is not a simple stacking of tools, but a scalable, iterable, and customizable full-stack system — the foundation of Sinovatio's AI applications and a core moat for the market.

Five Scenarios: Putting AI to the Test in Real Business

The faith in technology is ultimately validated by scenarios. Built on the DATA+AI foundation, Sinovatio has deeply rooted itself in core business scenarios including sales, quality inspection, external audit, R&D, and cybersecurity, developing several market-validated role-based AI Digital Twins. The core logic is simple: turn senior employees' experience, judgment, and professional intuition into digital capabilities usable by everyone in the enterprise.

• Sales AI Digital Twin: End-to-End Enablement of Opportunity Management — covering the full customer-follow-up process (opportunity entry, pre-visit preparation, script recommendation, requirement analysis, meeting minutes, CRM sync, and one-click weekly reports), distilling top salespeople's negotiation experience and on-the-spot adaptability into reusable organizational capability, opening the door to revenue growth.

• Quality Inspection AI Digital Twin: Quality Control with a Data-Detective Mindset — addressing the constraints of unmanageable test data, complex root-cause analysis, lagging process-drift warnings, and hard-to-pass-on expertise, it uses model training, RAG knowledge bases, and real-time data analysis to mine the correlations between test data and process parameters, freezing senior engineers' judgment rules and quality experience into model capability — "experience stays with the enterprise, capability is passed on" is no longer just a slogan.

• External Audit AI Digital Twin: Making Factory Audits Less Exhausting — intelligently consolidating audit materials across the board, automatically parsing review forms, filling in responses, and generating compliant documents; mature solutions can be reused with one click for similar customer audits, greatly reducing labor costs and time pressure, and unifying response standards — strengthening the enterprise's compliance defense.

• R&D AI Digital Twin: From Drawings to SOPs, Iteration No Longer Waits for Documents — using image recognition, topological sorting, and interference detection to automatically parse assembly drawings, organize parts lists, derive optimal assembly sequences, and auto-generate SOP documents and assembly guidance videos based on historical standards. Preparation cycles are shortened, new-product ramp-up is accelerated, and on-site assembly rework risk is significantly reduced — version mismatch risks are eliminated at the source.

• Security AI Digital Twin: Enabling Enterprises to "Use AI with Confidence and Digitalize Safely" — building a Defense AI Gateway that integrates three core protection mechanisms (data leakage prevention, key escrow, and code security auditing) to centrally govern all model invocation, plugin deployment, and agent operation inside the enterprise; complemented by specialized capabilities such as security operations scheduling, security incident investigation, penetration testing, and phishing drill exercises, it standardizes and automates network security operations while safeguarding the enterprise's data, systems, and intellectual property.

Sinovatio's AI capabilities have extended into industries such as food, daily chemicals, chemicals, and equipment manufacturing, completing validated deployments in scenarios including microorganism retrieval, formula generation, bulk procurement, equipment maintenance, and supplier risk management. The technical approach offers strong industry generality and scenario extensibility, with broad market growth potential.

The FDE On-Site Delivery Model: Closing the "Last Mile"

No matter how advanced the technology, if it cannot reach the business site, it is all talk on paper. The industry's chronic problem: technology teams understand algorithms but not frontline business pain points, while business people know operations but struggle to articulate their intelligence needs precisely. This two-way disconnect keeps good technology from becoming good outcomes.

Sinovatio's answer is FDE (Forward Deployed Engineer) — a composite team that is both proficient in Data+AI underlying technology, platform architecture, and algorithm logic, and deeply versed in the business details of industries such as manufacturing and services. They do not operate remotely from offices, but are stationed in workshops, R&D centers, and business departments, understanding pain points face-to-face and developing, debugging, deploying, and optimizing on site. The complete closed loop of "platform + AI Digital Twin + on-site delivery" truly closes the last mile of digitalization — every technology and every solution can genuinely take root in business and create value.

A New Starting Point: Value for Customers and Partners Alike

The comprehensive launch of the DATA+AI strategy is both a concentrated showcase of Sinovatio's years of technical accumulation and a new starting point for open collaboration across the industry.

Customer Perspective: Lightweight Transformation, Quick Wins Through Small Steps — abandoning "one-size-fits-all" large-system restructuring, customizing a gradual upgrade path based on enterprise size and business characteristics, requiring neither huge upfront investment nor long waiting periods — starting from a single role and a single scenario, moving fast and seeing results quickly. Core value: controllable risk · predictable cost · progressive results.

Partner Perspective: Co-Creating Industry Paradigms, Building a Digital Ecosystem Together — upholding an open-collaboration philosophy, exporting mature DATA+AI foundations, AI Digital Twin capabilities, and deployment methodologies, sharing industry experience, and jointly exploring innovative AI applications across verticals. Core value: technology output · experience sharing · ecosystem co-building.

Conclusion

The AI wave surges forward; the noise of concepts will eventually fade. Only tangible results and long-term value form the true foundation for navigating industry cycles. Sinovatio's DATA+AI strategy does not chase fleeting industry hype or pile up convoluted technical concepts, but chooses a simpler starting point — first make AI run in the workshop, on the production line, and within business flows, then refine it step by step. With data as the foundation, AI as the engine, and deployment as the direction.

Going forward, Sinovatio will continue to deepen enterprise digitalization, iterating technology, enriching scenarios, and improving services. In the new era of human-machine collaboration, we will move forward alongside customers and industry partners, co-building digital productivity and winning a digitalized future together. Pragmatism is the best form of long-termism.