Canada
Puerto Rico
USA
Belgium
France
UK
IndiaThe traditional prescription has been a full platform migration: tear out the old, install the new, and absorb two to four years of integration risk along the way. For most operators, that’s not a transformation plan. It’s a budget-cycle gamble. Industry data makes the stakes concrete: 19% of all software programs are canceled before completion, and 50% experience significant cost overruns.
Innova Solutions takes a different view. We call it the Sidecar Approach.
What the Sidecar Approach Is and What It Isn’t
Instead of rebuilding BSS/OSS stacks from the ground up, the sidecar approach deploys AI agents alongside your existing infrastructure. The agent operates as a lightweight process, reading signals from current systems, interpreting intent, querying back-end data, and acting, without writing to or restructuring the core.
Think of it as adding an intelligent layer to a system that already knows your business, rather than starting over with one that doesn’t. This is how Innova helps operators achieve modern AI performance on the platforms they already own.
The First Use Case: AI Sales Shadowing
The most immediate application is AI sales shadowing — and the productivity drag it eliminates is well documented.
In B2B telecom, sales reps routinely function as manual data intermediaries. A typical enterprise quote requires toggling between a CRM, a CPQ system, an inventory portal, and an engineering verification step — all to produce a proposal the customer expects within hours. That administrative load crowds out the work that actually closes deals: account strategy, competitive positioning, and relationship depth.
When an AI agent is deployed as a sidecar to the CRM, it shadows the rep’s activity in real time. As the rep works, the agent reads conversational signals, queries relevant back-end data, and surfaces proactive next-best-action recommendations, auto-populating technical specs for a fiber proposal, flagging contract misalignments, or identifying upsell opportunities that haven’t yet surfaced in the pipeline. The CRM is never upgraded; the sidecar makes it measurably smarter.
The Business Case
The sidecar approach trades infrastructure risk for deployment speed. Three advantages compound quickly:
Faster time to value
With no data migration and no core system restructuring, intelligent agents deploy in weeks. Productivity gains are visible before the quarter closes.
Lower total cost of ownership
Activated legacy data
An Architecture Built to Scale
Deploying a sales-shadowing agent is not just a productivity improvement: it’s an infrastructure decision. Once the sidecar architecture is established and governed, it becomes the foundation for every AI use case that follows: autonomous customer service diagnostics, AI-generated proposal content, and self-healing order management.
Telecom operators don’t need to rebuild their environments to operate like AI-native organizations. They need the right intelligence layer between what they have and what they want to do.
“The sidecar doesn’t replace your systems. It makes them perform like they were built last year.”
Next in this series — Part 2 of 4: How the same sidecar architecture eliminates the bespoke B2B proposal bottleneck, turning days of manual collateral production into a process measured in minutes.
Key Contributor: Dr. Sanjay Joshi, Senior Manager-Content, Research & Sales Enablement
