Make SAP Application Support Seamless and Effortless with Zinger

Incubated by SAP.io and used by SAP.

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Cut SAP Support Costs by 40% with Zinger

  • 24/7 Automated L0 Support
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    Zinger's SAP Support Bot can provide contextual response to 100% of L0 (informational) support queries.
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  • No need to write FAQs.
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  • Zinger automatically creates FAQs and KBs from support manuals, product documents, and training videos.
  • Deflect 50% of L1 calls
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    Zinger's SAP Support Bot can be trained to resolve 50% of repetitive L1 tasks using conversational prompts.
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  • No need to curate chat/call scripts.
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  • Zinger automatically creates formal KB notes, auto tags for issue type and root causes, and executes API calls to auto-resolve simple L1requests.
  • Reduce resolution time
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    ‍    Zinger's SAP Support Bot improves resolution time by 30% by automatically routing tickets to the right SME and bringing up similar tickets resolved in the past.
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  • No need to maintain look up tables.
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  • Zinger automatically tags and finds the right SME based on similar tickets resolved by the personnel and estimating bandwidth.

Heading

Utilizing Large language model automation like ChatGPT to provide your business with automated customer support - and if you don't take advantage of this opportunity, your competitors will. Don't miss out on the future of customer service - make use of this technology before it's too late.

Improve AMS margins by deflecting L0/L1 tickets. Reduce the cost of AMS support delivery and improve margins. Change the game. The transition from a people supports model to incident support model.

Improve AMS revenue and retention rate by expanding the scope of support. Provide end-to-end user support by responding to functional knowledge and process inquiry support, besides fielding technical questions. Own end-to-end user support and improve retention.

How does the Zinger’s Virtual Support Assistant (VSA) work?

SAP User on Teams, Slack, Web Chat Channel
Zinger’s LLM Based Virtual Support Assistant
SAP Support Staff on Ticketing System or Teams/Slack
SAP user chats with GPT based Support Assistant
GPT based Intelligent Chat Engine
Support SMEs provides Human Feedback to improve chat performance
Virtual Support Assistant responds to questions
Support and ticket Knowledge base
Support staff reviews automated responses and ticket performance
Virtual Support Assistant recommends actions
Zinger API action DB and action reco algo
Support Staff creates knowledge articles with action reference
User confirms actions and provides details to complete actions
Zinger generates forms and questions to capture details
Support Staff creates more APIs for automated execution
If the VSA is not able to respond or resolve the ticket, user creates a ticket.
Virtual Support Assistant completes the actions using APIs
Call, chat, and resolution steps gets recorded by staff for future reference
User can get into a live conversation with the Support Staff on teams
VSA identifies the right SME to route the ticket to
Support Staff on Live chat/Screen Share/ Call

How does Zinger’s SAP Support bot work?

Why SAP AMS Providers Should Prioritize AI-Based Support Automation ?

ChatGPT and Similar LLM models will automate support, eventually.
If you do not offer automated AMS support,your competitors will.
Stay ahead of your competitors in the AI game with Zinger.

Improve AMS margins by deflecting L0/L1 tickets.
Reduce cost of AMS support delivery and improve margins.
Change the game. Transition from people support model to incident support model.

Improve AMS revenue and retention rate by expanding scope of support.
Provide end to end user support by responding to functional knowledge and process inquiry support, besides fielding technical questions.
Own end to end user support and improve retention.

Our Solution: Digital Acceleration Platform

A conversational platform that responds, recommends, and helps execute in the flow of work
[on teams, Slack, Webex, SAP, Salesforce, Support Portal]

Inquiry Support

  1. Informational Query from Content
  2. Numerical Query from Databases
  3. Navigational Query from SME/ Link tagging
  4. Transactional Query from API documentation

Decision Support

  1. Diagnostic, Predictive, Retrospective Ticket analysis
  2. Recommend Insights Recurrences, Root causes, Actions
  3. Recommend Content Qualifying Questions, Docs/ taining
  4. Recommend People Support SME

Execution Support

  1. Collaborative Action
  2. Action Automation -API
  3. Action Assistance
  4. Conversation Apps
Pull
Push
Guided

Why use us over ChatGPT/large language models?

Providing comprehensive support for informational, numerical, navigational, and transactional inquiries
Recommending what to do and how to do it, as well as who can assist in resolving the issue.
Utilizing transaction APIs or in-platform workflows to automatically resolve issues.
Automatically escalating to the appropriate SME for faster resolution.
Adapting to new tickets as they are resolved.
Analyzing prevalent issues and root causes to better estimate resolution time.

Secure Your Workflows with Strategies to Mitigate the Risks of Generative AI.

Increase Accuracy and Reduce Hallucinations through Pre-Processing and Confidence Filtering.
Enhance User Confidence by Routing to the Source of Truth Page or Paragraph.
Minimize Prompt Engineering Support to Prevent Injection Attacks.
Enhance Performance with Enterprise Language, Context, and Role-Based Personalization.
Improve Response Quality with Qualifying Questions for Context and Intent Disambiguation.
Enhance Privacy with Downloadable LLM Models (If GPT is Not Approved).

Transform Your Workflows with Specialized AI Processing and Automation Powered by AIOps

Maximize Your Efficiency with Auto Tagging for Content and Context Tags.
Quickly Find Answers with Q&A Pair Extraction from Long Format Documents and Call Scripts.
Leverage Blended Retrieval Methods with Semantic, Keyword.
Full Text and Generative Context Question Generation.
Enhance Your Results with Learn to Rank and Reinforcement Learning with Human Feedback.
Get Highly Personalized Results from Profiling and Usage.

Why use us over ChatGPT/large language models?

Providing comprehensive support for informational, numerical, navigational, and transactional inquiries

Recommending what to do and how to do it, as well as who can assist in resolving the issue.

Utilizing transaction APIs or in-platform workflows to automatically resolve issues.

Automatically escalating to the appropriate SME for faster resolution.

Recommending what to do and how to do it, as well as who can assist in resolving the issue.

Utilizing transaction APIs or in-platform workflows to automatically resolve issues.

Secure Your Workflows with Strategies to Mitigate the Risks of Generative AI.

Increase Accuracy and Reduce Hallucinations through Pre-Processing and Confidence Filtering.

Enhance User Confidence by Routing to the Source of Truth Page or Paragraph.

Minimize Prompt Engineering Support to Prevent Injection Attacks.

Enhance Performance with Enterprise Language, Context, and Role-Based Personalization.

Improve Response Quality with Qualifying Questions for Context and Intent Disambiguation.

Enhance Privacy with Downloadable LLM Models (If GPT is Not Approved).

Transform Your Workflows with Specialized AI Processing and Automation Powered by AIOps

Maximize Your Efficiency with Auto Tagging for Content and Context Tags.

Quickly Find Answers with Q&A Pair Extraction from Long Format Documents and Call Scripts.

Leverage Blended Retrieval Methods with Semantic, Keyword.

Full Text and Generative Context Question Generation.

Enhance Your Results with Learn to Rank and Reinforcement Learning with Human Feedback.

Get Highly Personalized Results from Profiling and Usage.

Why Emplay?

You need a problem solving m/c, not an answering m/c.
You need to mitigate the risks of Generative AI
You need Specialized AI Processing and AIops automation
One stop shop for informational, numerical, navigational, and transaction inquiry
Reduce Hallucination inaccuracy via Pre-processing +confidence filtering
Auto Tagging(content tags, context tags)
Recommends what to do next, how to do, and who can help solve the problem
Improve user confidence by routing to source of truth page/paragraph
Q&A Pair extraction from long format document/ call scripts
Auto-resolves by calling transaction APIs or executing in-platform workflows
Limit prompt engineering support to prevent injection attacks
Blended Retrieval methods-Semantic, Keyword, Full text, and Generative
Auto-analyzes top issues and top root-causes to estimate resolution time.
Fine tune for enterprise language, context, and role- based personalization
Personalization- profile and usage
Auto-escalates to the right SME for faster resolution
Improve response quality by asking qualifying questions for context and intent disambiguation
Context question generation- role, region, topics, collateral type
Auto-learns for new tickets resolved.
Alternate downloadable LLM models to reduce privacy violation(If GPT is not approved)
Learn to rank, reinforcement learning with Human feedback

Why Emplay ?

Reason #1
‍
You need a problem
solving machine,
not an answering machine.

Provides single interface for information, numerical, navigational, and transactional inquiry support.
Recommends what to do next, how to do, and who can help solve the problem
Auto-resolves by calling transaction APIs or executing in-platform workflows
Auto-analyzes top issues and top root-causes to estimate resolution time.
Auto-escalates to the right SME for faster resolution
Auto-learns for new tickets resolved.
Reduce Hallucination inaccuracy via Pre-processing +confidence filtering
Improve user confidence by routing to source of truth page/paragraph
Limit prompt engineering support to prevent injection attacks
Fine tune for enterprise language, context, and role- based personalization
Improve response quality by asking qualifying questions for context and intent disambiguation
Alternate downloadable LLM models to reduce privacy violation(If GPT is not approved)

Reason #2

You need to mitigate
the risks of
Generative AI

Reason #3

You need Specialized
AI Processing and
AIops automation

Auto Tagging(content tags, context tags)
Q&A Pair extraction from long format document/ call scripts
Blended Retrieval methods-Semantic, Keyword, Full text, and Generative
Personalization- profile and usage
Context question generation- role, region, topics, collateral type
Learn to rank, reinforcement learning with Human feedback

Learning, Support, and Transaction Assistant

Conversational Learning Assistants
provide personalized onboarding
support, query support and recommendations
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Help your customers and users with adoption and change management

Learn More

Conversational Support Assistants
provide 24/7 automated L1 ticket resolution support. It self learns from tickets, call scripts, and manuals.

Help your customers and support team deflect 50% of L1 calls

Conversational Transaction Assistants
help execute SAP and other system transactions using conversational prompts. It can read API documents to self train itself.

Help your customers accelerate their Digital Transformation Efforts.

Learn More
‍

Other SAP use-cases.
HR Support Desk

Answer extraction from policy, learning, and HR process documentations to respond to employee queries 24/7.

Route questions to the right HR personnel, peer, support desk. Learn from human responses.

Respond to employee data queries from HR and other work systems
e.g. how many personal days do I have?

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