AI-built CRM hardened for Cloud production
A CRM prototype built with an AI tool, re-architected with secure auth, a real database, environment separation, CI/CD, monitoring, and backups — then deployed on the cloud.
We don't invent fake clients, logos, revenue, or testimonials. The following are illustrative example workflows and reference architectures until real client case studies are published.
Each panel is an illustrative build — the kind of work we do, framed as an example workflow or demo, never a fabricated client outcome.
A CRM prototype built with an AI tool, re-architected with secure auth, a real database, environment separation, CI/CD, monitoring, and backups — then deployed on the cloud.
A unified AI support layer: a website chat widget and an inbound call agent, both grounded in a knowledge base, creating tickets and escalating to humans with full context.
A reference production deployment: CI/CD pipeline, Postgres with automated backups and restore testing, CDN, centralized logging, monitoring, and alerts.
A struggling SaaS diagnosed across app, database, and infrastructure: query and index tuning, deployment fixes, and a cost review that cut waste while improving performance.
The blueprints behind the example workflows — production topologies we stand up and harden.
VPC, Postgres with automated backups and restore testing, CDN, CI/CD via pipeline, centralized logging, monitoring, alerting, and secrets management with IAM least privilege.
Knowledge-base-grounded chat widget and inbound voice agent, ticket creation, analytics, and confidence-based human escalation — with guardrails and full transcripts.
Labels such as “Example workflow” and “Demo case study” are used deliberately until real client case studies are available to publish.