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Put your data to work with generative AI on AWS

We design and build production-grade AI solutions on Amazon Bedrock — connected to your real data, integrated into your workflows, and built to deliver business value from day one.

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The opportunity

Generative AI that works on your data — not generic demos

Most generative AI projects stall because the model is disconnected from the data that actually matters. A chat interface over a generic LLM is not a business solution — it's a proof of concept with no path to production.

Cloudwalker builds generative AI solutions on Amazon Bedrock that are grounded in your existing AWS data infrastructure — Redshift, S3, Glue, and your operational databases. We connect the model to real, governed data and build the retrieval, validation, and prompt engineering layers that make AI responses accurate and trustworthy.

Our flagship product, Echo, is a conversational analytics engine built on exactly this architecture — natural language queries translated to Redshift SQL, with business-friendly responses delivered in seconds. We build the same pattern for clients across betting, financial services, and logistics.

100% AWS-native stack — Amazon Bedrock, Redshift, S3, Glue. No external LLM APIs.
<3s Typical response time for natural language to Redshift SQL queries in Echo
eu-central-1 All data stays in Frankfurt — no PII leaves your AWS region

What we deliver

Six generative AI capabilities we build for clients

Conversational analytics

Natural language queries translated to SQL against your Redshift or Athena data warehouse. Business users ask questions in plain language — the AI writes and runs the query, then explains the results. No SQL knowledge required.

Document intelligence

Retrieval-augmented generation (RAG) over your internal documents, contracts, and knowledge bases. Built on Bedrock Knowledge Bases with S3 as the document store — accurate, cited answers with no hallucination risk on facts.

AI-powered reporting

Automated narrative generation for operational reports — daily summaries, anomaly explanations, and trend commentary written by AI from your Redshift data and delivered to dashboards or via email on schedule.

Real-time event classification

Bedrock models integrated into Kinesis Firehose or Lambda pipelines for real-time classification, enrichment, and anomaly detection on streaming data. Fraud signals, player behaviour patterns, and operational alerts — processed as events arrive.

Guardrails & governance

Amazon Bedrock Guardrails configured to prevent hallucination, restrict topics, and enforce PII redaction. All model inputs and outputs logged to CloudWatch for audit. ISO 27001 aligned AI governance from day one.

Agent & workflow automation

Bedrock Agents orchestrating multi-step workflows — querying databases, calling internal APIs, and taking actions based on natural language instructions. Automate complex operational tasks without building custom orchestration logic.

How we work

From use case to production in four phases

1

Use case discovery

We spend the first week understanding your data landscape, your users, and the decisions they make manually today. We identify 2–3 high-value AI use cases with clear success criteria — not generic chatbots, but specific workflows where AI reduces time-to-insight or automates repetitive reasoning tasks.

Stakeholder interviews Data audit Use case scoring
2

Prototype & validate

A working prototype is built in 2–3 weeks against your real data. We test accuracy, latency, and edge cases with actual users — not synthetic inputs. Prompt engineering, schema context, and retrieval strategy are tuned until the output quality meets a defined acceptance threshold before moving to production.

Amazon Bedrock Claude Sonnet Bedrock Knowledge Bases Redshift
3

Production build

The validated prototype is hardened into a production system — CloudFormation IaC, IAM roles with least privilege, CloudWatch monitoring, Bedrock Guardrails, and a CI/CD pipeline. We build the API layer, the UI integration (or direct QuickSight embedding), and the operational runbook. No shortcuts that create technical debt.

AWS CloudFormation Bedrock Guardrails AWS Lambda Amazon API Gateway CloudWatch
4

Operate & evolve

Post-launch, we monitor model performance, query accuracy, and latency. As your data schema evolves, we update the context layer. As new Bedrock models are released, we evaluate and migrate where it improves quality or reduces cost. AI systems degrade silently without active maintenance — we prevent that.

Model evaluation Prompt versioning Cost monitoring Schema drift detection

Engagement models

Built for teams at different stages of AI adoption

AI product build Most popular
Discovery, prototype, production build, and launch
End-to-end delivery — we own the outcome, not just the code
CloudFormation IaC — your team inherits clean, maintainable infrastructure
Post-launch monitoring and model performance tracking
Knowledge transfer and operational runbook included

Suited to teams who want a production AI solution delivered by specialists. We build it, you own it.

AI advisory & acceleration
Architecture review of your existing AI/Bedrock implementation
Prompt engineering and retrieval strategy optimisation
Bedrock Guardrails and governance setup
Team upskilling on Bedrock, RAG patterns, and agent orchestration
Code review and production-readiness assessment

Suited to teams building their own AI capabilities who want Cloudwalker expertise on architecture, quality, and AWS best practice.

Echo
Cloudwalker's own conversational analytics product — live in production
100%
AWS-native — Amazon Bedrock, no third-party LLM dependencies
60+
AWS certifications across the Cloudwalker team
eu-central-1
All data and model inference stays in AWS Frankfurt — no cross-region transfer

AWS services we use

Amazon Bedrock Claude Sonnet (Anthropic) Bedrock Knowledge Bases Bedrock Guardrails Bedrock Agents Amazon Redshift Amazon S3 AWS Glue Amazon Kinesis AWS Lambda Amazon API Gateway Amazon CloudWatch AWS CloudFormation Amazon QuickSight

Ready to build AI that actually works?

Tell us about your data and the decisions you want to automate. We'll propose a use case and a path to production.

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