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Generative AI Sales Playbook
Sales Plays for 17 Generative AI Use Cases
Help customers see real ROI with generative AI on AWS
Gen AI transforms call centers by getting agents to the right information faster, summarizing previous calls, providing critical context, and sweeping knowledge bases for answers to help resolve the issue. Combining these AI capabilities with AWS services such as Amazon Lex and Amazon Connect call centers can streamline interactions and ensure precise, consistent, and rapid customer service.
Ideal Customer Profile
Anyone with a large customer service business unit
Anyone operating a call center and looking to improve operations/efficiency
Verticals: Retail & CPG, Travel & Hospitality
How to Pitch
Generative AI can be adopted by call centers gradually, as there are many smaller use cases for it that can be combined
The faster an agent can answer or leave the answer entirely to an AI, the fewer agents it takes to effectively run the call center
This kind of automation means increasing the customer’s AWS footprint while simultaneously lowering their call center overhead
In order to execute on this use case, the customer needs a strong handle on retrieval-augmented generation, vector databases, and engineering to avoid hallucinations; Mission Cloud has done all of these
Ragnarock, Mission Cloud’s branded architectural approach, generates and embeds a large number of query variants into the model to ensure accuracy when generating answers
Mission Cloud built a solution to fully automate Workato’s IT help desk resolution process. Sagemaker and Bedrock provided the fully managed infrastructure, tools, and workflows. By leveraging generative AI, the automated solution was able to analyze an issue, make a diagnosis, and resolve how to correct the problem.
Some large language models operate by creating images instead of text. By pairing a foundation model like StableDifussion with SageMaker and Bedrock for training and S3 for storage, you can create an asset creation and management solution for creating, enhancing, and modifying product and marketing photography.
Ideal Customer Profile
Anyone looking to enrich their product photography or significantly scale up their asset pipeline
Anyone working with traditional photography workflows that could benefit from prototyping/experiment gains
AI-generated image applications are more than plunking a model down and prompting it; you need an experienced partner to create the right guardrails around what the model can generate to ensure brand appropriateness
Creating an interface that is easily operable by customer stakeholders is critical; we integrate AppDev developers to create custom UIs for our solutions
Customers need to know how to use more advanced modification techniques to get what they want, not just re-prompting; through knowledge transfer, we teach them how to own and operate the solution
Mission Cloud works backward with customers to incorporate gen AI into their existing workflows; opportunities to replace processes are great, but enhancing can matter just as much
Mission Cloud’s AI solution allows Mixbook customers to create customizable photo books with generated images set to recognize user preferences and context. New AI features include caption creation, storyline generation, embellishments, and autoscaling for printing. This customer use case was featured on AWS Innovate 2024.
Using AWS services such as Amazon Bedrock, SageMaker, OpenSearch, and Lambda functions with LangChain, you can create intelligent systems that automatically generate, modify, and optimize compliance documents based on a customer's specific controls, frameworks, and policies - dramatically streamlining the compliance documentation process.
Companies seeking to reduce manual effort in creating and maintaining compliance documentation
Businesses that need to customize policies based on in-scope and out-of-scope controls
Organizations with large volumes of compliance data stored across multiple systems
Verticals: Financial Services, Healthcare & Life Sciences, SaaS & Technology, Government Contractors
How to Pitch
Compliance documentation is often repetitive and time-consuming. This gen AI solution can reduce document creation time while improving accuracy and completeness
Unlike generic AI tools, with AWS you can build a solution specifically for compliance documentation, with safeguards to ensure generated content meets regulatory requirements
The system gets smarter over time as it learns from your existing policies, controls, and documentation
Mission's Ragnarock architecture includes RAG (Retrieval-Augmented Generation) techniques to prevent hallucinations and ensure factual accuracy when generating policy documents
Built on AWS's native services, the solution provides enterprise-grade security and scales with your compliance needs, while integrating seamlessly with your existing data sources
Mission Cloud helped Drata automate compliance document creation across 17 different frameworks. Using AWS services like Bedrock, SageMaker, and OpenSearch with vector embeddings, they built a system that automatically generates policy content based on a customer's in-scope and out-of-scope controls. This solution recommends which policies should link to controls and suggests appropriate modifications to existing documentation. The AI-powered approach dramatically reduced manual compliance documentation effort while maintaining accuracy and consistency, enabling Drata's customers to manage their compliance requirements more efficiently.
Confidential - For AWS Only
AWS Services
Amazon Bedrock*
Amazon SageMaker*
Amazon OpenSearch
AWS Lambda
Amazon DynamoDB
* Qualifies for double revenue
Sales Play
Drug Discovery
1-Liner
Accelerate and reduce costs in the drug discovery process through molecule generation, predictive models, data analysis, and personalized medicine.
Ideal Customer Profile
Pharmaceutical companies looking to streamline their drug discovery process
Biotech startups seeking to leverage AI for innovative drug development
Research institutions aiming to accelerate their molecular studies
Healthcare organizations interested in advancing personalized medicine
Companies with large datasets of molecular and clinical information
Verticals: Pharmaceuticals, Biotechnology, Healthcare, Academic Research
How to Pitch
Showcase acceleration: AWS's high-performance computing and machine learning services can significantly speed up molecule generation and screening, potentially reducing years from the drug discovery timeline
Highlight cost-effectiveness: AWS's scalable infrastructure for computationally intensive tasks allows companies to allocate resources more efficiently
Demonstrate advanced analysis: AWS's AI and analytics services can analyze vast datasets to identify patterns and potential drug candidates that human researchers might overlook
Emphasize customization: Building on AWS enables companies to tailor AI models for their specific drug discovery needs and easily adapt as research evolves
Stress security and compliance: AWS's robust security features and compliance certifications are crucial for protecting sensitive research data and meeting regulatory requirements in pharmaceutical development
Mission Cloud collaborated with Soley to enhance its drug discovery processes on AWS, focusing on building a modern data architecture to support projected growth. This included improving performance, data governance, ETL performance, and ML process and analytics agility. Mission Cloud assisted in understanding current data infrastructure, defining data pipelines, implementing data warehousing, reviewing ML models and potential use cases, designing ML workflows, and developing concepts for ML Ops.
Confidential - For AWS Only
Sales Play
Dubbing and Translation Pipelines
1-Liner
Using AWS services like Polly, Transcribe, and Translate, along with an LLM, you can create an automated dubbing and translation pipeline for taking any content and recreating it in another language.
Ideal Customer Profile
Anyone with an international audience (or looking to expand to one)
Anyone already utilizing a traditional dubbing / translation pipeline for content or with a large content backlog they plan to translate
Verticals: TMEGS, Travel, Communications, and eLearning businesses
How to Pitch
The efficiency gains are so large that they enable customers to pursue global audiences much earlier and grow faster
This lets customers take risks in untested markets at a much lower entry price
Generated voice fidelity is rapidly improving—we are already trying approaches that can emulate particular emotional tones, affects, and speaking cadences
As higher fidelity markets adopt these technologies, like feature films or triple-A gaming, partners that can integrate AWS’s native ML stack, advances in NLP, and LLMs will build the best pipelines
Mission Cloud has developed a solution that allows MagellanTV to expand its international presence and audience efficiently while delivering high-quality, accessible content. The solution proficiently translates and dubs English documentaries into any language, using multiple workflows: English-to-English translation of slang and idioms, sentence shortening after translation, and cultural sensitivity. MagellanTV has gained significant cost savings, bringing translation costs for documentaries from $20 per minute to $1 per minute.
Leveraging AWS services such as Amazon Bedrock, SageMaker, and Amazon Polly, you can create interactive AI-powered interview simulations that transform traditional selection-based education into natural, conversational learning experiences. These solutions enhance skill development through realistic scenarios while providing detailed assessment and feedback capabilities.
Ideal Customer Profile
Educational institutions seeking to modernize traditional case-based or scenario-based learning
Organizations that train professionals in high-stakes fields requiring complex decision-making (healthcare, legal, financial advising)
Education software companies looking to integrate AI capabilities into existing platforms
Programs where "queuing" (providing multiple-choice options) limits authentic skill assessment
Verticals: Healthcare & Life Sciences, Education Technology, Professional Services Training, Financial Services
How to Pitch
Traditional selection-based educational tools inadvertently provide hints—our conversational AI approach creates realistic scenarios where learners must demonstrate authentic reasoning without prompts
By combining Amazon Bedrock, AWS Fargate, and SageMaker, we create systems that not only simulate realistic interactions but also assess decision-making patterns and reasoning quality
Mission's expertise ensures AI models are properly trained with domain-specific knowledge and realistic case scenarios
Unlike generic chatbot solutions, our approach can be designed to identify and test for edge cases or rare conditions that are critical in fields like healthcare
The solution is extendable - starting with interview simulations that can later incorporate visual elements, assessment dashboards, and comprehensive learning management features built on AWS
Mission Cloud partnered with DxR Development Group to modernize their clinical training platform with AI capabilities. By leveraging AWS services, they transformed traditional case-based learning into an interactive, AI-powered experience where medical students develop clinical reasoning skills through natural language patient interviews. This eliminated "queuing" where listed questions inadvertently prompt students, creating more authentic assessment. DxR's new platform, targeting a January 2025 release, combines metahuman interfaces with AI chatbot technology, revolutionizing medical education and improving patient outcomes.
Generative BI is truly an application of generative AI models to typical business intelligence workflows to enhance those workflows by making them more powerful, accessible, and meaningful.
Ideal Customer Profile
Organizations with large volumes of complex data seeking deeper insights
Companies looking to democratize data access across various departments
Businesses struggling with traditional BI tools' limitations in data interpretation
Organizations aiming to make data-driven decisions more quickly and accurately
Verticals: Finance, Healthcare, Retail, Manufacturing, and Technology
How to Pitch
Showcase how AWS's AI services can transform traditional BI into an interactive, conversational experience, making data insights accessible to non-technical users across the organization
Emphasize the ability to generate natural language explanations of complex data trends, helping decision-makers understand insights more quickly and thoroughly
Demonstrate how generative BI on AWS can uncover hidden patterns and correlations in data, potentially leading to new business opportunities or efficiency gains
Highlight the advantages of building a custom solution on AWS, including full data control, seamless integration with existing systems, and the flexibility to adapt to unique business needs - benefits not typically available with off-the-shelf AI BI solutions
Stress the scalability and real-time processing capabilities of AWS, enabling faster decision-making as the company's data needs grow
Mission Cloud collaborated with FalconX to develop an AI-driven visualization solution for near real-time market data. Leveraging AWS infrastructure, they integrated services like Amazon Bedrock and Amazon SageMaker. This solution empowered FalconX traders to receive dynamic visualizations summarizing market insights instantly, showcasing the potential for powerful analysis without manual coding.
Sales Play
Intelligent Document Processing
1-Liner
Intelligent document processing (IDP) works with document data using machine learning techniques, AWS Services like Textract and Comprehend, data analytics, and large language models to help with tasks that might otherwise require human readers or writers.
Ideal Customer Profile
Anyone doing mission-critical work on large volumes of paperwork and relying on manual processes/people to get it done
Anyone whose business is rate-limited by their ability to process paperwork
Verticals: Legal, Healthcare & Life Sciences, Fintech & Finance
How to Pitch
These solutions can save customers $$$ while getting them more invested in AWS, and Mission Cloud has built many of these solutions before
We only use AWS-native ML services and prefer Bedrock for accessing LLMs
We maintain compliance and privacy standards when working with sensitive documents—and we can meet these standards even when working with an LLM
The customer gets a turnkey solution that meets their accuracy, throughput, and other output criteria
Mission’s practice builds it all—from the underlying data architecture all the way through to prompt tuning and LLMOps for post-launch
Mission Cloud helped RecordBoss automate document summarization for their level three products, cutting costs and reducing manual effort. By using natural language processing algorithms, they efficiently handled various document types and structures. This automated process not only saved RecordBoss money by eliminating expensive manual reviews but also improved efficiency, enabling quicker decisions on case viability and freeing up resources for other critical tasks.
Query your organizational knowledge from a single UI by having a natural language conversation with a chatbot. With AWS services like Amazon Lex, Amazon SageMaker, and AWS Lambda in combination with open-source agentic frameworks like LangChain and techniques like retrieval-augmented generation, AI-powered platforms can disseminate organizational knowledge more effectively than ever.
Ideal Customer Profile
Anyone looking to enrich their product’s interactivity
Anyone who’s product has a steep learning curve
Anyone with a knowledge or data-oriented product (dashboards, visualizations)
Anyone looking to improve their customer support experience
Anyone with a large amount of institutional knowledge/data they’d like to make more accessible
Verticals: Retail & CPG, ISV, DNB
How to Pitch
Internal tooling can be a low-risk first project candidate; once accuracy has reached an acceptable threshold, you can easily graduate to a customer-facing interface
In order to execute on this use case the customer needs a strong handle on retrieval-augmented generation, vector databases, and engineering to avoid hallucinations; we’ve done all of these
Ragnarock, Mission Cloud’s branded architectural approach, generates and embeds a large number of query variants into the model to ensure accuracy when generating answers
Fexa turned to Mission Cloud to build a generative AI solution that could help reduce the number of maintenance service calls that can be answered and solved in a quicker, less expensive way. Mission Cloud used Amazon Bedrock, Anthropic Claude 2, and Amazon Kendra for the AI model, while Streamlit facilitated the front-end interface, and LangChain served as an orchestrator to bring everything together. The solution saved both time and money for Fexa and its customers, inspiring further innovation and optimization within the platform.
Some customers require a model specifically trained over their dataset to significantly change the model’s responses, biases, and effectiveness for a particular type of work.
Ideal Customer Profile
Customers already attempting to train their own models and are comfortable with the associated costs of training and hosting
Anyone working on the very outside-of-the-box use case requiring extreme specialization or novel machine-learning techniques in their model
How to Pitch
Doing this effectively requires having an extensive familiarity with AWS’s data services and how to rapidly move large amounts of data between end points; Mission’s practice is end-to-end, encompassing everything from data architecture to model ops, and gives a customer all the skills they need to do this
Mission has done this work before at the scale necessary to actually train a model
Mission Cloud helped the company transition from Google Cloud Platform to Amazon Web Services for cost-effective large language model training. This solution seamlessly integrated with the company's existing training framework, lowered training costs for their LLM and reduced loading times by 50%.
Confidential - For AWS Only
Sales Play
LLMOps
1-Liner
LLMOps use the same skillset and types of work as in a typical ML Ops engagement but specialize around the particular care needed for developing, training, fine-tuning, and maintaining a large language model.
Information about the Ideal Customer Profile and How to Pitch for this use case will be available soon.
The Mission Cloud team helped Bearing AI to assist in utilizing Sagemaker for their model's training and deployment. We supported large-scale distributed training on multiple instances with multiple GPUs and also provided assistance on the model development and feature engineering side.
Confidential - For AWS Only
Sales Play
Market Surveying
1-Liner
Transform complex survey data into actionable insights through an AI-powered natural language interface that automatically generates analytical code, visualizations, and business intelligence without requiring technical expertise.
Ideal Customer Profile
Organizations that conduct large-scale market research and customer surveys
Research teams struggling with the technical complexity of survey data analysis
Companies seeking to democratize data insights across non-technical teams
Businesses looking to reduce the time from data collection to actionable insights
Verticals: Retail & CPG, Financial Services, Healthcare & Life Sciences, Media & Entertainment, Software, Travel & Hospitality
How to Pitch
Traditional survey analysis requires technical skills in statistical programming - this solution lets anyone ask natural language questions and receive instant visualizations and insights
Unlike static analytical tools, this solution gets smarter over time, adapting to your specific business language and metrics
Built with a sophisticated architecture featuring pre- and post-processing steps that ensure reliable, accurate results even when analyzing complex survey data
The solution includes self-correction capabilities that enable it to handle edge cases and unexpected data patterns autonomously
Mission developed a natural language analytics solution for Prodege, transforming how market research teams interact with survey data. Using Amazon Bedrock with Claude-3 models, the system allows non-technical users to ask questions in plain English and receive instant visualizations and business insights. The solution automatically identifies relevant data columns, generates appropriate analytical code, and presents findings through intuitive visuals and summaries. This eliminated the need for specialized programming skills, dramatically accelerated insight generation, and enabled Prodege to process complex survey data more efficiently while controlling costs through optimized AWS infrastructure.
Confidential - For AWS Only
AWS Services
Amazon Bedrock*
Amazon SageMaker*
AWS Lambda
Amazon EC2
Sales Play
Marketing Personalization & Automation
1-Liner
Gen AI not only lets you create marketing content—it helps you completely personalize content, like avatars/digital humans and podcasts, and improve marketing automation. With gen AI, you can react in real time to changes in customer sentiment by integrating with AWS services like SES, Pinpoint, Kinesis, and Lambda.
Ideal Customer Profile
Anyone with a high CAC (Customer Acquisition Cost)
Anyone looking to improve their DemandGen capabilities
Anyone in a market that values response time for winning deals
Rather than outsourcing to a SaaS, this builds the customer's marketing automation on AWS natively
Creates a far more scalable way to segment audiences, even to the point of making atomic, per-individual segments
Helps a customer leverage audience data that might be hard to use (unstructured data) and build more meaningful profiles / segments
Mission Cloud can help build systems to automate how content is differentiated on a per-customer basis
Mission Cloud created an AI generated video and audio solution for the MBA team that allows users to clone their voices, create avatars/digital humans, and generate scripts that would be representative of a celebrity.
Ragnarock is the framework for best practices we’ve developed through building generative AI solutions on AWS. It is a combination of several techniques, a common set of patterns, and an overall architecture we’ve found particularly efficient, accurate, and effective when building generative AI solutions. The name itself is derived from the combination of Retrieval-Augmented Generation, a Neoteric* Agent, and Amazon Bedrock (RAG-NA-rock).
Target Solutions
Knowledgebases & Knowledge Management
AI Assistants
Chatbots
Customer Support
Search & Research Tooling
Generative BI
Any Solution Using Agent Capabilities
How to Pitch
Ragnarock is a cost-efficient, accurate, and secure way to build generative AI agent solutions
By keeping all traffic local to AWS, we can greatly improve a solution's speed while also keeping data private and secure
By using this pattern, customers can leverage data they already host on AWS to improve an agent's reasoning and research capabilities
This pattern is a breakthrough in agent accuracy and flexibility; by using semantic distillation and meta-prompting, we greatly expand capability of an agent to accurately respond to a user's intent and interests
Generative AI allows companies to improve their recruiting workflow and enhance candidate search accuracy and recommendations. By generating summaries and scoring systems, it streamlines tasks, improves candidate matching, and personalizes experiences. This optimization leads to increased efficiency and data-driven insights, marking a significant improvement in the recruitment process.
Ideal Customer Profile
Companies with high-volume hiring needs or frequent recruitment cycles
Organizations looking to modernize their HR and recruitment processes
Businesses struggling with long time-to-hire or high cost-per-hire metrics
Companies in competitive industries where talent acquisition is critical
Verticals/Industries: Tech, Healthcare, Finance, Retail, and Professional Services
How to Pitch
Emphasize customization: AWS services enable tailored recruiting solutions that adapt to unique processes and evolving needs, unlike rigid off-the-shelf options
Highlight data control: Building on AWS ensures full ownership of sensitive recruiting data, addressing privacy concerns common with third-party solutions
Showcase scalability: AWS's pay-as-you-go model allows the solution to grow cost-effectively with the company, avoiding long-term commitments
Stress seamless integration: Custom solutions on AWS can easily connect with existing systems, preventing data silos
Demonstrate the potential for continuous innovation: As AWS regularly releases new AI/ML services and features, companies can easily incorporate these advancements into their recruiting solution, staying ahead of the curve
Mission Cloud worked with Jobvite to develop an AI-powered interview question generator utilizing large language models. Mission built out the underlying architecture for the interview question generator and reviewed outputs for consistency, fairness, and relevance to the job description. The solution allowed users to upload job descriptions and resumes and receive a list of questions tailored to their needs.
Detect sensitive elements in images such as PII, automatically remove or blur these elements to ensure privacy, or even insert non-sensitive content into the image where this sensitive information was removed, to maintain the integrity of the image.
Ideal Customer Profile
Organizations handling large volumes of images containing potentially sensitive information
Companies in industries with strict privacy regulations or data protection requirements
Businesses seeking to automate their image anonymization processes
Organizations looking to share or publish images while protecting individual privacy
Verticals: Healthcare, Finance, Legal, Government, Media & Entertainment
How to Pitch
Emphasize flexibility: The solution allows customization to detect and handle various types of sensitive information based on specific needs and industry requirements
Stress integration and adaptability: Building on AWS provides fine-grained control over the anonymization process, easy integration with existing workflows, and the ability to adapt to evolving privacy regulations
Showcase intelligent manipulation: Demonstrate advanced features like context-aware blurring and AI-driven content replacement, which preserve image integrity and aesthetics while ensuring robust privacy protection
Showcase accurate detection: AWS's AI services like Rekognition and SageMaker can precisely detect and locate sensitive information in images, ensuring thorough privacy protection
Highlight automation: AWS Lambda and Step Functions create a scalable, serverless workflow for efficiently processing large volumes of images
Ideal Image, a prominent medspa brand, is working with Mission to enhance user experience with the use of generative AI. The solution will allow clients to upload images, specify desired improvements, and visualize potential procedure results, thereby differentiating Ideal Image and improving client outcomes.
Confidential - For AWS Only
Sales Play
Video Storytelling
1-Liner
Create compelling short-form video highlights automatically by leveraging AWS Bedrock with Nova AI models to analyze full-length content, identify the most engaging moments, and extract them as impactful clips without manual editing.
Ideal Customer Profile
Sports teams, leagues, and organizations with extensive video content
Media companies seeking to increase audience engagement through highlight clips
Organizations with limited video editing resources but high content output needs
Verticals: TMEGS, Education
How to Pitch
Manual video editing for highlights is time-consuming and resource-intensive - building a gen AI solution on AWS can automatically identify and extract the most engaging 6-second clips from hours of content
The solution leverages Amazon's Nova AI models to understand video content context and identify key moments based on action, audience reaction, or other engagement signals
Unlike generic video editing tools, our approach is specifically designed to understand what makes content compelling to viewers, driving higher engagement metrics
By automating the highlight creation process, organizations can significantly scale their content production without expanding editing teams
Mission's expertise in implementing AI workflows ensures a solution that integrates seamlessly with existing content management systems
Mission partnered with WePlayed Sports to automate the creation of impactful 6-second sports highlights from longer videos. Using AWS Bedrock's Nova AI models and Lambda for intelligent workflow coordination, the solution automatically identifies the most exciting moments in sports content without manual editing. This POC enables sports organizations to streamline content production, enhance fan engagement, and maximize the value of their video assets by efficiently extracting compelling highlights that capture the most engaging action. The system's ability to identify key moments helps WePlayed Sports deliver more engaging content while reducing production time and resources.
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