Reported impact
Business outcome
Continuing to Scale Rapidly on AWS Based on its first 3 months on the market, Scenario hopes to soon be a household name in the gaming industry.
- Productivity Improvement
- Scalability
- Speed to Market
AWSSoftware / SaaSCloud NativeGenerative AI / LLMMedia and ContentProductivity ImprovementScalabilitySpeed to Market2023 AWSAWS#ff9900Software / SaaSglobal“That’s not the core of what an artist in the gaming industry wants to do.” Because AI is not inherently creative, Scenario needed its solution to be simple for customers to interact with.After launching its beta in December of 2022, Scenario scaled to over 40 countries in 3 months.Jun 21, 20236AWS Batch · Amazon API Gateway · Amazon ECS0 2023-06-21 6
Scenario
“That’s not the core of what an artist in the gaming industry wants to do.” Because AI is not inherently creative, Scenario needed its solution to be simple for customers to interact with.
After launching its beta in December of 2022, Scenario scaled to over 40 countries in 3 months.
Continuing to Scale Rapidly on AWS Based on its first 3 months on the market, Scenario hopes to soon be a household name in the gaming industry.
Hervé Nivon Co-Founder and Chief Technology Officer Building a Generative AI Offering in 2 Months Using AWS Batch Scenario built its solution exceptionally fast.
“Our company has served and generated millions of images with only three people, proving a new use case for generative AI with little time and effort.” As of March 2023, Scenario provides customers with approximately 100,000 images each day.
Solution
Game development company Scenario Incorporated (Scenario) wanted to reduce time to market for game studios by using generative artificial intelligence (AI) to create style-consistent assets, but it had to deliver fast to meet industry demand for its offering. To get its product up and running quickly, Scenario committed to going all in on Amazon Web Services (AWS). The company used Amazon Elastic Container Service (Amazon ECS), a fully managed container orchestration service, to build its generative AI offering. Using AWS CDK to Accelerate Cloud Development Scenario was founded to revolutionize the way in-game and marketing assets are produced for studios.
Solution architecture
- Compute
- Amazon ECS Runs containerized application workloads and batch simulations.
- Serving
- Amazon API Gateway Publishes and secures APIs that front application and model services.
- Orchestration
- AWS Batch Schedules and optimizes large-scale batch and model-training jobs.
Architecture clues
- “The strategy was to use AWS services that reduce the development workload and are simple to maintain, while meeting low-latency and availability requirements,” says Nivon.
Evidence from the source
For example, without the assistance of AI, game artists spend valuable time on repetitive tasks to mass-produce assets for their games.
This time could be spent to create more original visuals that attract players and make games more engaging.
Using AWS CDK to Accelerate Cloud Development Scenario was founded to revolutionize the way in-game and marketing assets are produced for studios.
“It’s super time consuming for game artists to generate assets, edit them, send them for approval, and go back and forth with their colleagues,” says Marie Gerard, head of growth at Scenario.
“That’s not the core of what an artist in the gaming industry wants to do.” Because AI is not inherently creative, Scenario needed its solution to be simple for customers to interact with.
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
How scores are calculated
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Customer reference value86/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth15/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity16/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact25/253 metrics describe measurable impact.
- Deployment scale10/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence85%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability21/2510 of 12 key fields link to a named source.
- Direct evidence20/205 direct source quotes retained.
- Date provenance8/10The publication date comes from publisher-controlled metadata.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity8/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://aws.amazon.com/solutions/case-studies/scenario-case-studyAWSFirst-party
Scenario customer story
Supports- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes
- Publication date
Date evidence
- Publisher catalog date Jun 21, 2023 · AWS · First-partyOpen date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.
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