What’s included
What’s included
Source consolidation
Bring the relevant sources together on AWS with pipelines that keep them current.
Built with
- Amazon S3
- AWS Glue
- Amazon OpenSearch Service
- Amazon Bedrock Knowledge Bases
Why it matters
Why it matters.
Retrieval quality, not model choice, decides whether a GenAI feature feels smart or feels broken.
Cleaning and structuring data once pays off across every use case that follows, instead of being redone per project.
Good lineage and labelling also make the security and compliance conversation far shorter.
What’s included · how it runs
Profile. Build. Validate. Operate.
Step 01
Profile
Map sources, measure quality and identify what the target use cases actually need.
What’s included
Source consolidation
Bring the relevant sources together on AWS with pipelines that keep them current.
Step 02
Build
Stand up the pipelines, transformations and vector or search layer on AWS.
What’s included
Cleansing and structuring
Deduplication, normalisation, chunking and metadata design tuned for retrieval.
Enrichment
Embeddings, classification and labelling so content is findable in the way your use case queries it.
Step 03
Validate
Test retrieval quality against real queries and tune chunking and metadata.
What’s included
Quality controls
Automated checks, lineage and monitoring so quality does not quietly decay.
Step 04
Operate
Hand over monitoring, alerting and the runbook for keeping data fresh.
What you walk away with
- AI-ready data pipelines on AWS
- Retrieval layer tuned to your use cases
- Data quality checks and monitoring
- Documentation and handover runbook
Case studies
Customers we’ve delivered this for.
Draft · pending HES approval
Case studyHuman eSources
Make the hiring call with AI.
How Human eSources turned nearly three decades of talent science into AI that explains every job match, live on Amazon Bedrock behind TruTalent, its new recruiting platform.
- Industry
- HR tech, talent assessment
- We built
- Talent Scout AI
- Runs on
- Amazon Bedrock
Keith Gaudreau
VP Product Strategy
Case studyMould Detect AI
Computer vision for mould detection.
[How the client got the outcome: what Assembly built and where it runs. One sentence.]
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Case study[Client]
[The promise] [in 2 lines].
[How the client got the outcome: what Assembly built and where it runs. One sentence.]
Talk to an engineer[Client logo][First Last][Role]
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