Deal Scale
Work type: Built Lifecycle: Growth / Scale Card copy: Built a multi-tenant AI sales platform from product workflows through production infrastructure.
Deal Scale grew from a focused sales automation product into a larger AI sales platform. Because it is one of our own products, we have been able to work across the entire stack rather than handing off after the first release.
The application brings lead ingestion, enrichment, scoring, CRM synchronization, AI follow-up, workflow automation and analytics into one system. We built the surrounding infrastructure so those features could operate across different customers, data sources and automation providers without turning every account into a separate engineering project.
As the system grew, the work shifted toward the same problems our Growth and Scale clients run into: background jobs, event-driven workflows, observability, data isolation, permissions, retries, failure handling, integrations and infrastructure that can grow without rewriting the product.
The platform now includes multi-tenant architecture, RBAC, workflow orchestration, vector search, production telemetry, autoscaling, exportable logs and support for white-label deployments.
Deal Scale gives us a case study where we can show the engineering decisions behind the interface. We can expose architecture diagrams, workflow examples, observability, integration patterns and the tradeoffs that came with moving an AI product from early development into a larger production system.
What we owned
- Full-stack product engineering
- AI and agent workflows
- Backend architecture
- CRM and API integrations
- Data pipelines
- Workflow orchestration
- Vector search
- Observability
- Multi-tenancy and RBAC
- Infrastructure and deployment
