Running the Full Sales-to-Hire Funnel on Echo

These Echo customer case studies show how Taller's AI platform applies relationship intelligence, sourcing, and sales workflows across staffing and professional-services organizations.

Taller's own business had the same operational challenges Echo was designed to solve for clients. Sales, sourcing, matching, proposals, and hiring workflows lived across separate tools, including a standalone ATS. That fragmentation created slower time-to-hire, manual proposal work, inconsistent candidate matching, and no single source of truth across the full funnel.

There was also a strategic contradiction. As the company building Echo, Taller could not credibly position the platform as the operating layer for staffing and professional-services firms while continuing to run its own business on someone else's stack.

Taller adopted Echo across its full sales-to-hire funnel. The company uses the same modules it sells to clients: Sales for relationship and pipeline management, Solutioning for matching talent to client needs and building the case for each candidate, and Sourcing for AI matching across Taller's own candidate base.

Echo also supports proposal generation, allowing Taller to create on-brand proposals inside the platform instead of assembling them manually. In parallel, Taller is migrating off its existing ATS so Echo becomes the single system of record for the entire revenue and delivery funnel.

Taller has improved time-to-hire, increased candidate-match accuracy, and accelerated proposal turnaround. The company is also migrating off its ATS to run solely on Echo.

Taller running its own business on Echo is the clearest possible proof of confidence in the product. Echo is not only a platform Taller sells; it is the operating system Taller uses to run its own staffing and delivery workflows.

Strategically, this matters because Echo's product direction is grounded in lived operating experience. Taller is its own first customer, which means the platform is continuously tested against real sales, sourcing, solutioning, and hiring pressure. The product improves not as a theoretical AI tool, but as a system used to run a services business every day.