Case Studies
Work that speaks for itself.
Real engagements. Real outcomes. Across AI transformation, platform engineering, M&A, cloud, and data.
AI Transformation

DPL Financial Partners
AI Agents Across the Full Software Development Lifecycle — Deployed in Under Three Months
DPL Financial Partners wanted to find out how much of their software development lifecycle could be accelerated and improved with purpose-built AI agents. In under three months, Mashbot deployed agents across every phase of the SDLC — from business requirements capture through testing — fundamentally changing how their engineering and product teams worked.
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Fortune 500 Industrial Manufacturer
AI-driven quality inspection reduced defect escape rate by 74%
A Fortune 500 industrial manufacturer needed to modernize quality control across 12 production facilities. We designed and deployed an AI-powered visual inspection system integrated into existing production lines, paired with a predictive maintenance model that reduced unplanned downtime.
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Platform Engineering

PE-Backed SaaS Platform
Platform re-architecture enabled 10x scale and cut deployment time from days to minutes
A PE-backed B2B SaaS company was hitting the ceiling on its monolithic platform — deployments took days, scaling required manual intervention, and engineering velocity had stalled. We re-architected the platform for scale while keeping the business running.
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Mid-Market Financial Technology Firm
Internal developer platform cut onboarding from 3 weeks to 2 days
A mid-market fintech company was losing engineering talent to larger competitors and struggling to onboard new hires efficiently. We built an internal developer platform that transformed developer experience and became a competitive advantage for recruitment.
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Mergers & Acquisitions

Fortune 1000 Industrial Conglomerate
Clean technology separation completed 3 months ahead of TSA deadline
A Fortune 1000 industrial conglomerate divested a $400M division. We led the technology carve-out — from due diligence support through TSA exit — delivering a fully independent technology environment three months ahead of the contractual deadline.
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PE Portfolio Company — Healthcare IT
Three-platform integration delivered $4.8M in annual technology synergies
A PE-backed healthcare IT company acquired two competitors within 12 months. We led the technology integration program that consolidated three separate platforms into a unified product, unlocking the synergies that justified the acquisition multiples.
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Cloud

Lifeworks
Legacy on-premises infrastructure migrated to AWS with zero customer-facing downtime
Lifeworks needed to migrate its core platform from aging on-premises infrastructure to AWS to support product growth and reduce operational overhead. We led the migration strategy and execution, delivering a modern cloud architecture without disrupting the customer experience.
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Fortune 500 Energy Company
Cloud cost optimization program delivered $3.6M in annual savings without compromising performance
A Fortune 500 energy company had migrated to the cloud two years prior but was spending 40% more than projected. We conducted a comprehensive cloud optimization engagement that reduced costs by $3.6M annually while improving performance and reliability.
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Data

San Diego Gas & Electric
Enterprise data platform modernization enabled real-time grid analytics and regulatory reporting
San Diego Gas & Electric needed to modernize its data infrastructure to support real-time grid analytics, regulatory reporting automation, and the data foundation for future AI initiatives. We designed and implemented a modern data platform that unified disparate data sources and reduced reporting cycles from weeks to hours.
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Regional Financial Services Firm
Enterprise data governance program reduced regulatory findings by 85% and enabled self-service analytics
A regional financial services firm with $12B in assets under management faced mounting regulatory pressure over data management practices. We designed and implemented a comprehensive data governance program that resolved compliance gaps and unlocked self-service analytics for the business.
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Ready to redesign how your enterprise works?
Let's talk about where AI fits into your organization — and where it doesn't yet.
FAQs
Common questions about how we work, what we build, and what it takes to move from experimenting with AI to operating with it.
It means going beyond buying AI tools. AI transformation is about redesigning how your organization works — restructuring workflows, redefining roles, deploying agents and custom models, and building the governance infrastructure to manage it all at enterprise scale.
Using ChatGPT or Copilot is a starting point, not a strategy. A transformation partner helps you move from ad hoc AI usage to systematic integration — purpose-built agents embedded in your workflows, custom models trained on your data, and governance frameworks that make it all enterprise-safe.
Agents handle specific tasks — analyzing data, routing requests, generating reports. Infrastructure is everything that keeps those agents reliable, compliant, and maintainable: monitoring, audit trails, access controls, model versioning, and the orchestration layer that ties them together.
Governance is built into every engagement from day one. We design audit trails, access controls, data handling policies, and compliance frameworks tailored to your industry — whether that’s SOX, HIPAA, SOC 2, or internal enterprise standards.
We work primarily with technology companies, large enterprises, and PE/VC-backed portfolio companies across finance, healthcare, telecommunications, manufacturing, and professional services. Our approach adapts to any regulated or complex enterprise environment.
It depends on scope. A focused agent deployment can take 4–8 weeks. A full workflow redesign with custom model development and governance infrastructure is typically a 3–6 month engagement. We scope every project during the Visualize phase before committing to timelines.
Both. For many use cases, fine-tuned versions of leading foundation models deliver excellent results. For enterprises with proprietary data and domain-specific requirements, we develop fully custom models. We recommend the right approach based on your data, use case, and cost considerations.
We integrate with your team, not replace them. Our engagements are designed to build internal capability — we work alongside your engineers, transfer knowledge throughout the process, and leave your team equipped to maintain and evolve the systems we build together.
Visualize: we map your current operations, identify AI opportunities, and design the target state. Realize: we build and deploy agents, models, and infrastructure. Optimize: we monitor performance, refine workflows, and scale what’s working. Each phase has clear deliverables and decision points.
Schedule a consultation. We’ll discuss where your organization stands today, where you want to go, and whether Mashbot is the right partner to get you there. No pitch decks — just a conversation about your business.
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