Platform Engineering
Scalable platforms. Secure pipelines. Production-ready.
We design and build the platforms, pipelines, and developer infrastructure that let your teams ship faster without sacrificing security or reliability. From SaaS product architecture to DevSecOps, we engineer the foundation everything else runs on.
Move fast. But build on something that lasts.
Iteration isn’t an excuse for a weak foundation. The teams that ship fastest are the ones who invested in architecture that doesn’t need to be rewritten every 18 months. We build platforms, pipelines, and product infrastructure designed to scale with your ambition — not collapse under it.
Security isn’t a gate at the end. It’s built into every pipeline.
DevSecOps isn’t a buzzword — it’s the difference between shipping with confidence and shipping with crossed fingers. We embed security into CI/CD from the first commit, so your teams move fast without creating the vulnerabilities that slow everyone down later.
Platforms are products. Treat them that way.
Internal developer platforms deserve the same rigor as customer-facing products: clear interfaces, self-service provisioning, documentation that doesn’t require a Slack thread to decode. We build platforms your engineers actually want to use.
Our platform engineering expertise
Building a SaaS product that works for 10 customers is engineering. Building one that works for 10,000 is architecture. We design multi-tenant systems that isolate data without duplicating infrastructure, APIs that third parties actually want to integrate with, and the operational scaffolding — feature flags, usage metering, tenant management — that turns a product into a platform. Whether you're launching v1 or re-architecting for the next order of magnitude, we build for the scale you're heading toward, not just the traffic you have today.
Talk to usEvery manual deployment is a risk. Every security scan that happens after merge is a vulnerability window. We build CI/CD pipelines where security scanning, compliance checks, and automated testing are native to the workflow — not bolted on after the fact. Infrastructure as code so environments are reproducible. Policy as code so governance scales with the team. The result: your engineers deploy with confidence, your security team sleeps at night, and your release cadence is measured in hours, not quarters.
Talk to usDeveloper experience isn't a nice-to-have — it's a force multiplier. When engineers spend 30% of their time fighting tooling, waiting for environments, or decoding tribal knowledge, you're paying senior salaries for junior productivity. We build internal developer platforms with self-service provisioning, golden paths for common workflows, service catalogs, and documentation that stays current. The goal: every engineer on your team can go from idea to production without filing a ticket or joining a waiting queue.
Talk to usCase Studies
Our Platform Engineering Work
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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Insights
Our Platform Engineering Insights
API Design for Enterprise Systems: Principles That Last
DevSecOps: Integrating Security Without Slowing Down
Observability Engineering: Beyond Logs, Metrics, and Traces
Developer Experience: The Competitive Advantage Nobody Talks About
The Pendulum Swing: From No-Code to Pro-Code in the Age of AI
CI/CD Pipeline Design: From Commit to Production in Minutes
Site Reliability Engineering: Building Systems That Stay Up
Infrastructure as Code: Beyond the Basics
Ready to Build Your AI Roadmap?
Tell us where you are. We'll tell you what it takes to get where you're going.
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.
Still have questions?
Tell us what you're working on. We'll tell you if we can help.