Christopher Manavi

I’m Christopher Manavi, a Houston-based Forward-Deployed AI Solutions Engineer, AI-native product builder, and founder/operator focused on turning ambiguous business problems into practical AI workflows, automation systems, and revenue-generating software concepts.

My work sits at the intersection of AI solutions engineering, enterprise workflow automation, revenue operations, growth systems architecture, and full-stack product prototyping. I specialize in identifying hidden operational leverage inside businesses, mapping fragmented workflows, and rapidly prototyping software systems that connect front-end user experiences, backend logic, APIs, databases, CRMs, and automation tools into one usable operating layer.

As an independent product and workflow systems architect, I have designed and prototyped applied AI and PropTech systems across real estate technology, hospitality, geospatial intelligence, identity resolution, CRM automation, buyer-intent capture, and local-service revenue pipelines. My projects include AI-assisted product deployments such as TerritoryOS, a geospatial homeowner-intelligence and outreach system; SmartTourOS, a virtual-tour attribution and buyer-intent platform for real estate agents and lenders; and automated quote-recovery workflows for high-ticket home services.

Before focusing fully on AI-native systems, I founded and scaled Soda Stays, a tech-enabled hospitality platform operating hundreds of short-term rental units across multiple states. In that role, I built and managed growth systems across Google, Expedia, Airbnb, Vrbo, direct booking channels, vendor operations, guest communication, and revenue optimization. That founder/operator background gives me a practical understanding of how software, automation, and AI must connect to real business outcomes—not just technical demos.

Earlier in my career, I built search-driven growth and digital acquisition systems across real estate, online media, and local-service markets. My background includes technical SEO, organic acquisition, conversion architecture, audience growth, CRM logic, lead routing, and revenue operations. I bring that commercial lens into AI implementation, helping teams move from scattered tools and manual processes into integrated workflows that improve speed, visibility, and execution.

I am especially interested in forward-deployed AI engineering, where technical builders work directly inside business problems: discovering the real operational bottleneck, designing the system around user behavior, prototyping quickly, and aligning the final workflow with executive goals, compliance requirements, and measurable financial impact.

My technical and product fluency includes React, TypeScript, Vite, Tailwind CSS, shadcn/ui, Supabase, PostgreSQL, REST APIs, webhooks, Zapier, Make, HubSpot, Salesforce, Stripe API, Google Analytics, Lovable, Cursor, Claude, and OpenAI APIs. I use AI-assisted development tools to accelerate product validation, build working prototypes, and translate business requirements into clear architecture for engineering teams.

I studied at the University of California, Berkeley, earned a bachelor’s degree, and completed first-year legal coursework at Northwestern University Pritzker School of Law. That combination of business building, technical systems thinking, growth strategy, and legal/compliance awareness informs how I approach AI product architecture today.

I’m currently focused on helping companies design and deploy AI-native workflows, CRM automation, PropTech systems, RevOps infrastructure, and practical AI products that turn complex operational problems into scalable execution systems.