Business iteration is fast
Application development and modification cycles struggle to match the pace of front-end business, and high-frequency scenarios often rely on temporary spreadsheets and manual follow-up.
Internet industry
Bringing AI into commercialization, customer service, and e-commerce collaboration
Targeting high-frequency collaboration scenarios such as commercialization, customer service, e-commerce, and supply chains, Deneb helps internet companies unify fragmented processes, distributed systems, and real-time collaboration into a single AI-native platform, enabling rapid application delivery, end-to-end closed-loop processes, and real-time data accumulation.
Industry pain points
Internet companies grow rapidly, iterate scenarios quickly, and have many systems, while frontline teams heavily rely on mobile platforms and instant messaging tools for collaboration. Traditionally, online documents, IM, customer service systems, e-commerce systems, and approval systems are scattered, which easily leads to information omissions, untraceable processes, and insufficient collaboration efficiency.
Decentralized collaborative processes
Processes rely on online documents and instant communication tools for circulation, making data accumulation difficult, permissions unified, and responsibilities unclear.
Low cross-system efficiency
Customer service, e-commerce, compensation, and operations systems are fragmented, and cross-system collaboration requires manual copying, forwarding, and verification.
Data calibers are not uniform
Data on leads, orders, fulfillment, compensation, and complaints are scattered, making it difficult for business analysis to promptly reflect the true situation.
AI is difficult to enter the business
General Q&A struggles to directly call business systems and processes, making it impossible to form an auditable and reviewable execution closed loop.
Key points for plan construction
Empowering AI to understand business, call systems, and drive action
Quickly set up applications
Low-code and Ontology templates support the rapid launch of high-frequency business scenarios, reducing redundant development and temporary system construction.
Unified collaborative entrance
Connecting IM, mobile, PC, and business lobby to bring processes from communication tools into business systems.
End-to-end closed-loop processes
Linking customer service acceptance, approval, payment, fulfillment, complaint handling, and data archiving into a traceable chain.
Real-time operational insights
Accumulate transaction, fulfillment, compensation, customer service, and operational data to form real-time analytical capabilities for management.
AI assistants can perform the task
Let AI assistants initiate processes, generate summaries, identify risks, and drive action based on permissions, rules, and business objects.
The role of the platform: turning AI into an enterprise that can be operated, audited, and reused
Use unified Ontology, system connectivity, multi-agent capabilities, and low-code capabilities, AI moves from the Q&A entry point into the internet business field.
Touchpoint: Enterprise AI digital workbench
For commercialization, customer service, operations, e-commerce, and management teams, it offers AI Kanban, AI data inquiry, digital employee collaboration, as well as integration with PC, mobile, and IM.
Application layer: AI-native business systems
Centered on high-value internet scenarios, processes such as data, knowledge, and collaboration are accumulated into configurable and reusable business applications.
Ontology Engine: Enterprise business semantic layer
Through objects, attributes, relationships, actions, functions, process rules, security, governance, and publishing, AI understands the true semantics of industry business.
AI intelligence and construction
Supports agent decision-making meetings, digital employee management, identity and memory, tool integration, permission governance, model usage, and low-code generation.
Knowledge and system integration
Connects RAG's unstructured knowledge base with existing systems such as IM, e-commerce, customer service, finance, OA, and data platforms, creating a closed loop of business data, system knowledge, and process actions.
Cloud Market: Reusing enterprise AI assets
Accumulate Ontology industry template libraries, Skill marketplaces, workflow templates, knowledge packs, API action libraries, Agent templates, application templates, and governance strategy libraries.
Key capabilities for solution implementation
From business understanding to closed-loop action
Enterprise Ontology Construction
Unify influencers, leads, customers, orders, compensation, complaints, tasks, channels, and business metrics into a business target network understandable by AI.
Process orchestration
Through APIs, forms, approvals, IM, and mobile components, high-frequency collaboration processes are transformed from communication records into system closed-loops.
AI assistant
Combining intelligent reporting, summary generation, risk identification, customer service Q&A, and operational insights reduces repetitive manual processing costs.
Data operations
High-frequency collaborative data is stored in real time on the business dashboard, supporting unified analysis of teams, channels, orders, compensation, and fulfillment.
Solution implementation path
A unified method facilitates investment evaluation, asset accumulation, and reuse across more industry scenarios.
01
Let's sort out high-frequency scenarios
Prioritize high-frequency, high-value processes such as influencer collaboration, refund and compensation, customer service tickets, and IM collaboration.
02
Establish business targets
Break down leads, influencers, customers, orders, compensation, complaints, tasks, and business metrics into objects, attributes, and actions.
03
Connect existing systems
Integrate IM, e-commerce, customer service, finance, OA, and data platforms to reduce duplicate data entry and manual synchronization.
04
Configure process applications
Configure forms, approvals, status flow, mobile entry points, and permission rules through low-code configuration.
05
Combined with AI capabilities
Access intelligent summarization, intelligent Q&A, risk identification, automated alerts, and operational insights.
06
Continuous replication and promotion
Replicate validated templates to more business teams to form reusable internet business application assets.
High-value business scenarios in the internet industry
Focusing on the core business chain of the current industry, we organize analysis, judgment, and execution into a reusable closed loop.
Collaboration with commercial influencers
E-commerce refund compensation
IM embedded business collaboration
Customer service ticket management is intelligent
Operations analysis dashboard
Collaboration with commercial influencers
Commercialization processes such as influencer acquisition, referrals, building connections, fulfillment, and complaint reporting change frequently, making it easy to break points when relying on manual follow-up.
Construction methods
Based on a unified process center and mobile entry points, a collaborative influencer application is built, accumulating fulfillment, complaint, and transaction data onto a unified platform.
Application process
Lead entry - > Influencer building alliance - > Cooperation follow-up - > Contract fulfillment promotion - > Complaint handling - > Data archiving - > Business analysis
Solution Effectiveness
- Shorten the launch cycle for high-frequency applications
- Reduce manual follow-up and information omissions
- Make fulfillment data trackable and reviewable
E-commerce refund compensation
Refunds, compensation, approvals, and customer service linkage flow across systems, resulting in slow processing and incomplete status updates.
Construction methods
Through process orchestration and system integration, customer service acceptance, claims approval, payment processing, and status writing are linked into a single chain.
Application process
Customer service acceptance -> Compensation form generation -> Approval -> Payment -> Status callback -> Data synchronization
Solution Effectiveness
- Compress end-to-end processing time
- Improving consistency in compensation rules
- Reduce manual checks and repeated communication
IM embedded business collaboration
A large number of tasks are initiated and advanced in chat, lacking unified status, permissions, and business records.
Construction methods
Embed process initiation, document processing, and pending reminders into enterprise collaboration entry points, reducing system switching and linked forwarding.
Application process
Initiate an application within IM -> Collaborator Processing -> Status Synchronization -> Data Archiving
Solution Effectiveness
- Reduce communication breakpoints
- Improving frontline collaboration efficiency
- Combined with conversational process initiation and intelligent Q&A capabilities
Customer service ticket management is intelligent
Customer service requests, complaint escalation, and compensation rules require quick judgment, while manual retrieval systems and historical records are costly.
Construction methods
Integrate knowledge bases, order systems, and customer service ticketing systems to configure digital customer service staff and risk grading rules.
Application process
Customer Requests - > AI Summary - > Rule Matching - > Work Order Assignment - > Processing Closed Loop - > Review and Analysis
Solution Effectiveness
- Enhance consistency in customer service handling
- Reduce repeated Q&A
- Generate reviewable service quality data
Operations analysis dashboard
Channels, orders, compensation, customer service, and fulfillment data are scattered, making it difficult for management to spot operational deviations in time.
Construction methods
Unify the accumulation of operational indicators and business targets, build real-time operational dashboards and AI data query capabilities.
Application process
Data Integration - > Indicator Definition - > Kanban Configuration - > Exception Identification - > Task Assignment - > Effect Review
Solution Effectiveness
- Enhancing operational transparency
- Shorten the troubleshooting cycle
- Bring the analysis conclusions into the execution closed loop
Business value
From local efficiency improvements to measurable intelligent operations
Delivering value
Accelerate the launch speed of high-frequency business scenarios, reducing the costs of redundant construction and temporary system maintenance.
Synergistic value
Extract the collaboration process from chat records and online documents to form a traceable closed loop.
Operational value
Enhance operational efficiency through AI assistants, risk warning, and data analysis capabilities.
Governance value
Unify permissions, status, processes, and data accumulation to reduce caliber bias in cross-team collaboration.
Replicating value
Replicate validated high-frequency application templates to more teams and business lines.
The front desk team experiments faster
Scenarios such as influencers, customer service, e-commerce, and operations are rapidly launched, supporting continuous business iteration.
The collaborative process can be traced
Every circulation, approval, processing, and status writeback is recorded.
AI can enter the process
Q&A, summarization, recognition, and reminders are no longer limited to single-point capabilities, but move into business actions.
Management can see the data
From leads, orders, compensation to contract fulfillment, a unified business view is formed.
Building a closed-loop AI-native operation for the internet industry
Starting from a high-value scenario, accumulate replicable enterprise AI assets and gradually expand to more business units and operational scenarios.