ledin.pro

Cases

Below are selected cases where my role covered technical strategy, architecture, team leadership, and practical execution.

01

Algorithmics

EdTech for 1M+ graduates: AI, −30% infra, up to 2× time-to-market

Led an EdTech platform through a business split without losing stability for a 1M+ audience, introduced AI in support and engineering, improved time-to-market by up to 2×, and reduced infrastructure cost by 30%.

Primary outcome

Up to 2× faster time-to-market.

Additional outcomes

  • −30% infra, −20% IT services (~$100K/year).
  • AI agent in support: −20% cost.
  • Platform stable for 1M+ users through the business split.

Context

A large EdTech platform with significant traffic, complex infrastructure, and a large user base was going through major organizational and technical changes.

Challenge

The challenge was to preserve platform stability, accelerate delivery, adopt AI, and reduce cost without a disruptive platform rewrite.

What I did

  • Maintained a platform serving 1M+ users during a period of major change.
  • Introduced AI into support and engineering workflows.
  • Reduced infrastructure cost and dependency on foreign services.
  • Accelerated delivery through clearer technical organization and tooling.
Fractional CTOEdTech1M+ usersAI Transformation
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02

BotHelp

SaaS for 5,000 companies: 2× MRR, team 6→19, −30% infra

Scaled the engineering organization, doubled MRR through key integrations, grew the team from 6 to 19, and reduced infrastructure cost by 30% while load was increasing.

Primary outcome

2× MRR (WhatsApp + Instagram).

Additional outcomes

  • Engineering team 6→19.
  • −30% infra at 2× load.
  • 7× fewer incidents, <10 min response.
  • Bug reports −80%.

Context

A growing SaaS product needed a more mature engineering structure, key integrations, and stronger operational resilience.

Challenge

The team had to support growth, higher platform load, and major integrations without sacrificing quality or speed.

What I did

  • Scaled the engineering team from 6 to 19 people.
  • Delivered key integrations including WhatsApp and Instagram.
  • Improved observability and incident response speed.
  • Reduced infrastructure cost while the platform load increased.
Fractional CTOSaaSTeam ScalingIntegrations
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03

MetaPax

Deep-tech MVP in 2 months: $1M+ raised, 4× cheaper AWS

Built a deep-tech MVP in 2 months, assembled a team of 8 engineers, reduced AWS cost by 4×, and helped the product reach $1M+ in investment.

Primary outcome

$1M+ investment raised.

Additional outcomes

  • MVP in 2 months, engineering team of 8.
  • 4× cheaper AWS.
  • $2,000 streaming-glasses prototype for investor demo.

Context

The deep-tech team needed to reach MVP quickly and demonstrate product and technical viability to investors.

Challenge

The challenge was to assemble the team, bring the product to demo-ready state, and keep both infrastructure cost and delivery speed under control.

What I did

  • Assembled an engineering team of 8 people.
  • Built and launched an MVP for a real-time streaming product.
  • Optimized the backend running on AWS.
  • Prepared the technical foundation for investor demos and further product growth.
Fractional CTODeep TechMVPFundraising
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Michael Ledin

About me

Michael Ledin

A CTO with 16+ years of experience. I help product companies where they need technical strategy, architecture, team leadership, and practical AI adoption.

Fractional CTO / AI and architecture consultant

  • Fractional CTO and technical leadership.
  • AI transformation across product, support, and engineering.
  • Architecture modernization, reliability, and observability.
  • Infrastructure cost optimization.
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