Case Studies

Real results from real projects. See how we've helped companies transform their technology and operations.

$ terraform apply
✓ aws_lambda_function.api
✓ aws_s3_bucket.data
✓ aws_rds_instance.db
$ npm run deploy
✓ Build successful
✓ Tests passed: 847
✓ Deployed to prod
CLAUDE CODE
Engineering Fintech

Platform Modernisation

How Claude Code and custom AI agents helped us rewrite a legacy fintech platform in 16 weeks.

16 weeks 10x deployment speed
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SPEC-DRIVEN
Data Migration

Legacy ETL to dbt Migration

How AI agents helped migrate 200+ ETL jobs from SSIS, BODS, Informatica, and Talend to dbt in 12 weeks.

12 weeks €385K saved/year
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AI-POWERED
Blockchain Compliance

Crypto Compliance Infrastructure

How AI-driven automation helped a crypto custody provider pass their audit and scale 10x.

10 weeks 70% workload reduction
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LLM-POWERED
AI Operations

AI-Powered Customer Service

How we helped a retail brand automate 60% of customer service inquiries while improving satisfaction scores.

8 weeks +15 NPS points
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AI AGENT
Sales AI Agent

AI Business Development Agent

How we deployed Morgan, our AI BD agent, to run a client's entire outbound pipeline — from research to booked meetings.

6 weeks 47 meetings booked
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Engineering Fintech

Platform Modernisation

How Claude Code and custom AI agents helped us rewrite a legacy fintech platform in 16 weeks

16
Weeks
85%
Test Coverage
100+
Deploys/Week
3
Custom AI Agents

The Challenge

A Series B fintech was trapped by their 8-year-old monolith. Monthly deployments taking 4 hours. Engineers afraid to touch the codebase. No tests. No staging environment. All knowledge in 3 people's heads.

Our AI-First Approach

We used Claude Code throughout and built custom AI agents specifically for this codebase:

  • Deep Context First: Sophia, our Context Builder, spent 1 week documenting every process, stakeholder, and edge case — this became the AI's context
  • Custom AI Agents: Built codebase navigator, migration planner, and test generator agents
  • Quality Assurance: Elena, our Release Guardian, wrote comprehensive test suites and verified every migration step
  • Modern Stack: AWS Lambda, Terraform, GitHub Actions, ephemeral PR environments

The Results

  • ✓ Complete platform rewrite in 16 weeks (vs. 9-12 months quoted by others)
  • ✓ 85% test coverage (from ~5%)
  • ✓ Ephemeral PR environments for every pull request
  • ✓ Custom AI agents that still help the team today
"The AI agents they built understand our codebase better than some of our engineers. Traditional consultancies quoted 9-12 months. Waver Labs delivered in 16 weeks. The velocity we have now is how we're going to win."
Data Migration

Legacy ETL to dbt Migration

How AI agents and spec-driven development migrated 200+ ETL jobs in 12 weeks

12
Weeks
200+
Jobs Migrated
95%
Test Coverage
€385K
Annual Savings

The Challenge

A European insurance group had 15 years of ETL sprawl: SSIS packages from a team that left 5 years ago, SAP BODS jobs critical for regulatory reporting, Informatica mappings from 2010, and Talend jobs from a recent acquisition. No documentation. Comments in three languages. Zero tests. €400K annual licensing costs.

Our Spec-Driven Approach

We built a systematic migration factory using three specialised AI agents:

  • Documentation Agent: Powered by Sophia, our Context Builder, reverse-engineered every legacy job into structured specs — sources, transformations, business rules, lineage
  • Migration Agent: Generated dbt models from approved specifications, with custom skills for dbt patterns
  • Verification Agent: Elena, our Release Guardian, compared legacy output to dbt output, proving correctness before cutover

The Methodology

Specification first, code second. Every transformation went through: Document → Spec → Review → Generate → Verify. Business stakeholders approved specs before any code was written. 4 weeks of parallel running with zero unexplained discrepancies.

The Results

  • ✓ 200+ jobs migrated from 4 tools to 1 (dbt)
  • ✓ €385K annual licensing savings
  • ✓ 100% documentation (from ~10%)
  • ✓ 95% test coverage (from 0%)
  • ✓ New model delivery: 2 weeks → 2 days
  • ✓ 12 legacy bugs discovered and fixed during migration
"We'd been talking about migrating to dbt for three years. Every estimate came back at 12-18 months with a team of 6. Waver Labs did it in 12 weeks with AI agents that actually understood our legacy code. The documentation alone was worth the engagement — for the first time, we know what our pipelines actually do."
Blockchain Compliance

Crypto Compliance Infrastructure

How AI-driven automation helped a crypto custody provider pass their audit and scale 10x

10
Weeks
70%
AI-Automated
10x
Capacity Increase
85%
False Positive Reduction

The Challenge

A growing cryptocurrency custody company came to us 4 months before their first major regulatory audit. Their compliance team was drowning: 90% manual transaction monitoring, 3-5 day customer due diligence, and all knowledge in two analysts' heads.

Our AI-First Approach

We built AI-powered compliance infrastructure using Claude Code for development and Claude API for the runtime system:

  • AI Alert Triage: LLM pre-analyses every alert, suggests investigation paths, reduces false positives by 85%
  • AI-Generated Reports: One-click regulatory reports — what took hours now takes 2 minutes
  • Intelligent Case Management: AI auto-populates case files with relevant context
  • Continuous Learning: System improves weekly from analyst feedback

The Results

  • ✓ Passed regulatory audit with zero major findings
  • ✓ Alert investigation: 45 minutes → 5 minutes (AI-assisted)
  • ✓ Scaled capacity from 500 to 5,000 customers
  • ✓ Enabled expansion into 3 new EU jurisdictions
"Waver Labs showed us what AI-powered compliance actually looks like. The AI doesn't replace our analysts — it makes them superhuman. What used to take 45 minutes now takes 5. We passed our audit and now have infrastructure that can support 10x our current volume."
AI Operations

AI-Powered Customer Service

How we helped a retail brand automate 60% of their customer service workload

8
Weeks
60%
Automated
+15
NPS Points
4hrs
Response Time

The Challenge

A global consumer goods company was struggling with customer service scale. Response times had crept from 24 hours to 4-5 days. Customer satisfaction was dropping. The team was burning out.

Our Solution

We built an LLM-powered system that understands intent with nuance, responds in the brand voice, and knows when to escalate to humans. Smart triage, automated responses, and continuous learning from agent corrections.

The Results

  • ✓ Reduced response time from 4-5 days to 4 hours
  • ✓ 60% of inquiries handled automatically
  • ✓ NPS improved by 15 points
  • ✓ Team overtime dropped from 20 hrs/week to 2 hrs/week
"We were skeptical that AI could match our brand voice. Waver Labs proved us wrong. The system handles 60% of our volume with quality that matches our best agents."
Sales AI Agent

AI Business Development Agent

How we deployed Morgan to run a client's entire outbound pipeline — from research to booked meetings

6
Weeks
47
Meetings Booked
1,200+
Prospects Contacted
0
SDRs Required

The Challenge

A B2B SaaS startup had a great product but no sales team. The founders were doing outbound themselves — spending 15+ hours a week on research, emails, and follow-ups. They needed to scale pipeline without hiring an SDR team.

Our Solution: Morgan

We deployed Morgan, our AI Business Development agent, to run their entire outbound operation:

  • Prospect Research: Morgan identifies ideal customers from funding announcements, job postings, and industry signals
  • Personalised Outreach: Every email is researched and tailored — no templates, no spray-and-pray
  • Multi-Channel Follow-up: Automated sequences across email, LinkedIn, and phone
  • CRM Management: Pipeline updated in real-time, no manual data entry

The AI Reveal

Morgan discloses being an AI naturally in conversations. Rather than hurting response rates, it became a differentiator — prospects were curious and impressed. Several meetings were booked specifically because they wanted to see how it worked.

The Results

  • ✓ 47 qualified meetings booked in 6 weeks
  • ✓ 1,200+ personalised outreach messages sent
  • ✓ 12% response rate (3x industry average)
  • ✓ Founders reclaimed 15+ hours/week
  • ✓ Pipeline value: $2.3M in qualified opportunities
  • ✓ Cost: fraction of one SDR salary
"Morgan booked more meetings in 6 weeks than we did in the previous 6 months. The emails are better than what most humans write. And when prospects find out they've been talking to an AI, they're fascinated — it actually helps the conversation. We're never going back to doing outbound manually."

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