Case Studies

Documented results across AI systems and cloud infrastructure

A custom speech-recognition engine in production, $160K+ in annual AWS savings, and SOC2 compliance. Client names are withheld, and every number comes from a real engagement.

$160K+Documented Annual Savings
~106msp50 AI Inference Round-Trip
SOC2Compliance Delivered
15 YearsEngineering Experience
1
Key Result
1.6x Throughput at ~106ms p50

Custom ASR Engine for a Production AI Platform

Aipa (aipa.io), a commercial AI assistant I build and operateAI SaaSIn production

Challenge

Real-time voice features needed speech recognition with domain-specific vocabulary accuracy, strict latency budgets, and predictable GPU costs. Off-the-shelf transcription APIs could not meet all three requirements at once, so I built the engine.

Solution

  • Built a custom ASR engine on NVIDIA Parakeet (hybrid TDT+CTC), served from a NeMo container
  • Implemented decoder-level context biasing: a CTC word spotter grafts domain vocabulary into decoding, with per-word timings and confidence reporting
  • Migrated the encoder to bf16 behind strict evaluation gates: word-error-rate, biasing, and false-rejection parity, plus a live A/B on banked audio
  • Added TitaNet speaker embeddings (~12ms) for speaker-aware features
  • Built a restart-proof audio capture bank for continuous training data collection

Results

  • 1.6x throughput on the same GPU (RTFx 257 to 404)
  • p50 round-trip latency near 106ms through the serving gateway
  • Roughly 2GB of GPU memory freed per instance
  • Accuracy parity verified before rollout via live A/B on banked audio

Key Metrics

1.6x
Throughput gain
~106ms
p50 round-trip

Technologies Used

NVIDIA NeMoParakeet (TDT+CTC)PyTorchCUDATitaNetFastAPIDockerPython
2
Key Result
$100K+ Annual Savings

Infrastructure Optimization & Cost Reduction

Mid-size Educational Technology PlatformEducational Technology6 months

Challenge

Over-provisioned AWS infrastructure with high operational costs and inefficient resource utilization.

Solution

  • Implemented autoscaling policies for predictable user patterns
  • Refactored RDS configuration to Aurora with reserved instances
  • Created automation pipelines for on-demand developer resources
  • Executed migration from RightScale to AWS

Results

  • Over $100,000 in annual AWS cost savings
  • $30,000+ immediate savings from RightScale licensing elimination
  • Cut key page response times from roughly 2 seconds to 100ms
  • Reduced developer maintenance overhead
  • Improved resource utilization efficiency

Key Metrics

$100K+
Annual Savings
$30K+
Immediate Savings
2s → 100ms
Latency Reduction

Technologies Used

AWSAWS RDS AuroraMySQL MigrationAuto ScalingALBRoute53CloudFormationApache SolrMemcached
3
Key Result
SOC2 Compliance

VPC Security & Compliance Configuration

Grant Management PlatformSaaS Platform3 months

Challenge

Default AWS VPC configuration inadequate for security compliance requirements.

Solution

  • Designed compliant, modern cloud network architecture
  • Implemented advanced VPC and subnet configurations
  • Created segregated public and private subnet environments
  • Established comprehensive security group configurations
  • Implemented WireGuard VPN and site-to-site VPN tunneling

Results

  • Achieved SOC2 compliance requirements
  • Enhanced network security posture
  • Enabled secure office-to-cloud connectivity

Key Metrics

SOC2
Security Compliance

Technologies Used

AWS VPCSecurity GroupsWireGuard VPNNAT GatewayIPv6AWS IAMMFARoute53CloudFormation
4
Key Result
$60K+ Annual Savings

Full-Stack Infrastructure & Frontend Modernization

Consumer Media Platform (embedded principal engineer role)Consumer SaaSMulti-year

Challenge

Unstable legacy hosting led to frequent crashes, manual deployments, and inefficient resource use. The front-end codebase had diverged across multiple applications, slowing development and complicating maintenance. Delivered from inside the team as an embedded principal engineer.

Solution

  • Replatformed legacy hosting onto containerized, auto-scaling infrastructure (AWS ECS on Fargate)
  • Built branch-based CI/CD pipelines for reliable, automated releases
  • Secured infrastructure with VPN-only access, private subnets, and centralized controls
  • Unified a diverged legacy React codebase onto a single modern architecture
  • Managed third-party data-protection assessments and internal audits
  • Deployed CDN edge routing for improved global performance

Results

  • $60,000+ annual AWS savings
  • Stable, scalable containerized infrastructure
  • Consistent, modernized front-end stack
  • Stronger security posture with segmented access
  • Third-party data-protection audits passed

Key Metrics

$60K+
Annual Savings

Technologies Used

AWS ECSAWS FargateDockerCloudFormationAWS VPCCloudFrontS3CloudWatchRoute53ReactTypeScript

Company names are withheld. The Aipa engine is from my commercial product. The other results were delivered in full-time and embedded engineering roles; I now offer the same work as a consultant.

Have a similar problem? Get in touch.