Topic Signals
Rebuild business workflows with AI
From data acquisition and decision-making to content generation and system execution, we redesign workflows and put AI into real business systems.
From information to action, across the full AI workflow
A working AI system connects data, understanding, judgment, generation, execution, and continuous feedback.
- 01
Data acquisition
Web, APIs, documents, business systems, multimodal data
- 02
Understanding
Parsing, extraction, classification, linking, structuring
- 03
Decision-making
Rules, models, agents, human collaboration
- 04
Generation
Text, images, video, reports, code
- 05
System execution
APIs, CRM, ERP, business-system connections
- 06
Feedback and improvement
Monitoring, evaluation, attribution, optimisation
Featured cases
Starting with a concrete business problem, we turn AI into a system capability that keeps running.
Automotive Content Intelligence
Result
- Output significantly increased to 150+ articles/day
- Editor processing time dropped by 75%
What Changed
Improved both deduplication and value scoring, cutting duplicate materials by 84% and raising high-value topic detection by 91%
View Case DetailsNews Video Editing Workflow
Result
- Hour-level fast turnaround from topic to final video
- Unified shot rhythm and packaging boosted playback data by 16%+
What Changed
Connected semantic assetization, precise shot retrieval, visual planning, and editing review into an automated matching process for large-scale asset libraries.
View Case DetailsAI Video Editing Agent Cold-Start Growth
Result
- Organic clicks increased by 117% in the first two months
- Core keyword visibility achieved Google Page 1
What Changed
Aligned SEO, product messaging, and campaign creatives to help the AI video editing agent accelerate through cold start
View Case DetailsIndustry Intelligence Report Generation
Result
- Automated monitoring of 100+ data sources
- End-to-end automated generation of deep industry reports
What Changed
Connected unstructured data processing, structured storage, semantic retrieval, and report generation into a full pipeline for automated industry insights.
View Case DetailsBusiness workflows we rebuild
We start with frequent, complex, repetitive workflows and bring AI into understanding, judgment, generation, and execution.
Content Engine
Connect topic discovery, material integration, multimodal generation, human review, and multi-channel distribution into a continuous workflow that delivers text, image, audio, and video assets around the same topic.
Topic Clustering
Material Integration
Multimodal Generation
Quality Control System
Multimodal Distribution
Topic Signals
Topic Clustering
Material Integration
Multimodal Generation
Quality Control System
Multimodal Distribution
From an AI tool to a working business system
Enterprise AI can start with a task or involve a complete software system. Each approach solves a different layer of the problem.
Complete a task
For research, writing, analysis, content generation, and light tool use. A user starts the task and judges the result.
Best for personal productivity and lightweight workflows
Deliver a set of functions
Build pages, back offices, APIs, and business systems around clear requirements and stable rules.
Best for stable processes with clear rules
Rebuild a full business workflow
Start from business objects, rules, data, and collaboration. Design how AI, systems, and people decide, act, and improve together.
Best for cross-system enterprise workflows that keep running
Core capabilities for building AI business systems
From data to action, we break complex AI delivery into composable, reusable, and measurable engineering capabilities.
Data and system connections
Web / API, Database, CRM / ERP, ad platforms, documents / CAD, image / video
Understanding and analysis
Extraction, classification, entity resolution, knowledge graphs, RAG, risk detection
Judgment and collaboration
Agent, rule engine, planning, human-in-the-loop, approval, evaluation
Content generation
Text, image, video, reports, creative, code
System execution
API actions, batch operations, CRM updates, ad operations, notifications, workflows
Monitoring and improvement
Monitoring, logging, evaluation, attribution, optimisation
From a business problem to a working AI system
We start with the business workflow and progressively define, design, build, and improve the system.
Discover
Identify problems worth rebuilding with AI
Define
Define objects, rules, workflows, and success criteria
Design
Design agents, workflows, and system architecture
Develop
Build quickly with AI coding, integrations, and engineering
Drive
Monitor, evaluate, and improve continuously
Every project builds infrastructure for the next delivery
We turn repeatedly validated project capabilities into reusable business models and engineering assets.
Ontologies
Business objects, relationships, rules, and state models
Workflows
Business workflows that can be reused and composed
Skills
Atomic capabilities callable by AI agents
Adapters
Connections to business systems, platforms, and external APIs
Lingyi Labs
We turn emerging AI capabilities into working product prototypes that can be experienced directly.
CAD Studio
Extract structured information from engineering drawings and product data, then generate usable product content and assets.
Explore projectAI Intelligence Graph
Connect companies, people, events, and public information for ongoing monitoring, association analysis, and risk judgment.
Explore projectOpen Skills
Turn methods validated in real delivery into open Skills callable by AI agents.
Explore SkillsTestimonials
“We process a large amount of automotive material every day, and the slowest parts used to be deduplication, value judgment, and publishing priority. Lingyi Engine did not start by selling us a model. They first mapped how our editorial desk actually works, then put AI into the places where it could remove real manual load. Screening and publishing coordination are noticeably smoother now.”
“For news and financial video, the most time-consuming part isn't the edit itself—it's finding the right shots from tens of thousands of historical assets and matching them to the script. The system not only tags assets with fine granularity but also generates visual planning recommendations directly from voiceover semantics, saving the team massive amounts of time.”
“At Sparki's early stage, we did not need more polished pages for their own sake. We needed overseas users to understand the product faster. Lingyi Engine looked at SEO, landing-page messaging, and paid creatives as one growth loop. As priority keywords started moving up, trials and user feedback became easier to connect.”
Considering how to rebuild a business workflow with AI?
We can map the current process, systems, and data together, then identify where AI should contribute.
Contact uscontact@lingyilabs.com