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Sigma Trading Management provides trading operations services to online brokers running on MetaTrader 4 and 5. Every trading day, Sigma has to collect overnight financing rates ("swaps") from multiple liquidity providers, convert and mark them up correctly, and publish them to client platforms before a deadline that doesn't move. Jedi Hill built an agentic AI system, running on Amazon Bedrock, that has automated this process in production for the past four months — with zero

INNOWAVE, a high-throughput SMS/messaging (CPaaS) platform currently running on Alibaba Cloud, is planning a migration to AWS with a new managed Amazon Bedrock inference layer — designed by Jedi Hill to bring tiered generative AI capabilities to enterprise messaging at scale. The Challenge INNOWAVE operates a high-concurrency SMS platform (Spring Boot microservices on Kubernetes, with RocketMQ, MySQL RDS, Tair/Redis, and ADB) connecting to upstream carriers via SMPP/HTTPS, cu

Xenontech, a K-12 education technology platform serving schools across New South Wales, is preparing to move its AI infrastructure from Microsoft Azure and OpenAI to AWS Bedrock — with Jedi Hill designing and delivering the migration. The Challenge Xenontech's current AI capabilities run on Microsoft Azure infrastructure (VMs, Cosmos DB, Blob Storage) calling OpenAI's GPT-4 API. As usage has grown, three structural limitations have become clear: No tiered model routing. Every

A mid-size fintech enterprise was drowning in manual security reviews. Jedi Hill built an AI-powered threat modeling platform on AWS Bedrock that cut cycle time by 96% — without compromising security rigor. The Challenge Our client, a mid-size fintech enterprise operating in the digital payments and banking sector, runs a cloud-native platform that processes millions of transactions every day. Every new product feature had to pass through a rigorous security threat modeling r

Why we rebuilt AWS bill analysis as an AI problem instead of a spreadsheet problem. AWS Bill Analysis is an internal tool we built at Jedi Hill to read a cloud bill the way an experienced FinOps engineer would. It runs against single accounts and against Organizations multi-account setups, detects cost spikes, generates root-cause analysis and optimisation recommendations, and outputs a finished visual HTML report. The intent behind it is narrow and specific: move cloud cost

Cutting Cloud Costs for FX-Grade Infra How we saved $46,800/year for a regulated FX brokerage — without compromising a single trade. $28,300 → $24,400 13.8% Cost Reduction ~$46,800 Saved Per Year ABOUT THE CLIENT Sigma Trading Management (STM) is an ASIC-regulated B2B financial infrastructure provider serving Brokers, Market Makers, Exchanges, and Multi-asset Platforms across FX and multi-asset classes. Their AWS environment powers MT4/MT5 trading platforms, a proprieta

The AI era just made Infrastructure as Code non-negotiable. And I'm surprised more people aren't saying this. For AI agents to be useful in operations, they need to manage your infrastructure. Spin up environments. Resize clusters. Deploy services. Tear down staging stacks. But if your infrastructure lives in manual CLI commands, half-finished Terraform, and "ask Marcus on Slack" tribal knowledge — you've handed an AI agent a cockpit with no instruments. IaC was already worth

When VMware Licensing Becomes a Business Risk For many enterprises, the true cost of staying on VMware only becomes visible when the renewal invoice arrives. For FinLync — a global fintech company powering financial data integration for banks and financial institutions across Asia-Pacific — that moment arrived at exactly the wrong time. With over 200 engineers scaling a complex financial platform, FinLync was running 202 VMware ESXi virtual machines alongside 12 VMs on Alibab

The Security Bottleneck No One Talks About For fast-growing technology companies, security should be a competitive advantage — not a bottleneck. Yet for many enterprises, threat modeling remains one of the most time-consuming steps in the software development lifecycle. At one of our fintech clients in Asia-Pacific, the situation was critical. With over 200 engineers shipping new features across a complex financial platform, each threat modeling review required 8 to 12 weeks

You've set up a Spot Fleet with a few instance types. You've enabled Capacity Rebalancing. Your workload is still getting interrupted constantly. Here's what's actually happening. Spot interruptions don't happen one node at a time. When a capacity pool dries up — m5.large in us-east-1a, for example — every instance in that pool goes down together. You lose nothing for weeks, then 20 nodes disappear in the same minute. A fleet of 10x the same instance type in one AZ just means