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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.
Talk to our teamThe opportunity
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.
What we deliver
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.
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.
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.
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.
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.
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
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.
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.
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.
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.
Engagement models
Suited to teams who want a production AI solution delivered by specialists. We build it, you own it.
Suited to teams building their own AI capabilities who want Cloudwalker expertise on architecture, quality, and AWS best practice.
AWS services we use
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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