Building a serverless AI assistant at Pelago: concept to care in two weeks
At Pelago, a digital health company specializing in substance use disorder support, the engineering team found a way to build an AI-powered solution to address this challenge using AWS services in just two weeks. In this post, you will learn how Pelago used AWS serverless and AI services, such as Amazon Bedrock and AWS Lambda, to build and deploy an event-driven AI assistant. The result is a service that generates contextually aware suggested considerations for the care team.
- ▪At Pelago, a digital health company specializing in substance use disorder support, the engineering team found a way to build an AI-powered solution to address this challenge using AWS services in just two weeks.
- ▪In this post, you will learn how Pelago used AWS serverless and AI services, such as Amazon Bedrock and AWS Lambda, to build and deploy an event-driven AI assistant.
- ▪The result is a service that generates contextually aware suggested considerations for the care team.
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| Original publisher | AWS Architecture Blog |
| Canonical URL | https://aws.amazon.com/blogs/architecture/building-a-serverless-ai-assistant-at-pelago-concept-to-care-in-two-weeks/ |
| Publication time | Wed, 22 Jul 2026 17:12:27 +0000 |
| Retrieval time | 2026-07-26T10:01:46.686Z |
| Last seen | 2026-07-26T10:01:46.686Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 03NELwrajjso |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Building a serverless AI assistant at Pelago: concept to care in two weeks by Anton Aleksandrov, James Stratford, and Victor Jansson on 22 JUL 2026 in Customer Solutions, Serverless Permalink Share Healthcare organizations face a critical scaling challenge – how to maintain deeply personalized patient interactions as member bases grow, without overwhelming care teams or compromising quality. At Pelago, a digital health company specializing in substance use disorder support, the engineering team found a way to build an AI-powered solution to address this challenge using AWS services in just two weeks. In this post, you will learn how Pelago used AWS serverless and AI services, such as Amazon Bedrock and AWS Lambda, to build and deploy an event-driven AI assistant.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at AWS Architecture Blog.
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