Performance Agents draft evidence-backed plans from call data and track later behavior, with supervisors approving every plan.
By [RuntimeWire Staff](/author/runtimewire-staff)
· Published
Primary source: [PR Newswire](https://www.prnewswire.com/news-releases/observeai-launches-performance-agents-for-cx-to-transform-coaching-into-measurable-outcomes-302871705.html)
Why it matters #
Contact-center AI is moving from answering customers into managing the people who do. Observe.AI is betting supervisors will accept deeper automation when every plan still requires human approval.
Observe.AI CEO and co-founder Swapnil Jain launched Performance Agents on September 8, extending Observe.AI from analyzing customer conversations into drafting and measuring employee coaching.
The product follows the problem that led Jain into contact-center software nearly nine years ago. Jain grew up in Vidisha in central India, studied computer science at IIT Delhi and joined Twitter in San Francisco in 2012. He later helped establish Twitter's India office, then spent two years in India and Manila looking for a startup idea. Visits to large contact centers exposed manual reviews and outdated systems behind performance management.
Performance Agents turns that original observation into a larger product claim: interaction data can run most of the coaching workflow, provided a human manager remains accountable for the result.
The agents analyze conversation transcripts, quality-assurance scores and behavioral patterns across multiple interactions. They identify recurring issues, collect examples, draft a personalized plan and continue analyzing later conversations to see whether the targeted behavior changed. Observe.AI says supervisors can configure the system for a team, role, business line or employee cohort, including established coaching frameworks such as GROW and SMART.
Managers can review, edit, approve and share each plan. In its launch release, Observe.AI says Performance Agents do not make autonomous employment or performance decisions and that no plan reaches a frontline employee without human approval. Employees can see the evidence behind a recommendation, acknowledge the plan and add context to the record.
Observe.AI says a supervisor who previously spent 30 to 45 minutes searching calls, selecting examples and preparing notes can complete applicable workflows in under five minutes. That is an Observe.AI estimate, and the release does not specify which workflows qualify or how the timing was tested.
The deeper pitch concerns measurement. Contact centers have long counted completed evaluations and coaching sessions because those activities are easy to record. Jain wants Observe.AI customers to track whether an employee subsequently shows more empathy, handles objections differently, follows a required process or sets clearer expectations with customers.
Observe.AI's product explanation argues that ordinary QA scorecards often capture compliance without explaining why employees with similar scores produce different sales, retention or customer-satisfaction results. Performance Agents therefore treats behaviors such as active listening, discovery, ownership and de-escalation as measurable units alongside conventional QA requirements.
The September 8 release describes that workflow in detail. Observe.AI's claimed effects on retention, conversion, resolution rates or customer satisfaction remain unvalidated by independent data.
Human review is part of the product, not a disclaimer
The approval requirement matters because Performance Agents operates inside employee performance management. A model's interpretation of empathy, tone or active listening could influence coaching records and how managers view individual workers.
A uniform scoring rule may reduce differences between supervisors. It can also distribute a poorly defined behavioral standard across an entire workforce. Observe.AI's design keeps managers responsible for deciding whether the evidence is relevant, whether the recommendation fits the circumstances and what reaches the employee.
That control also gives frontline workers access to the interactions supporting a recommendation. Observe.AI says employees can add context rather than accept an unexplained score. The approach does not remove the risks of automated evaluation, but it creates a review trail around the output.
Performance Agents may also expose failures that coaching cannot fix. If one employee repeatedly misses a disclosure, an individual plan may be appropriate. If a whole group makes the same error, the cause could be a confusing policy, weak training or a broken internal process. Observe.AI says its Insights Agents can identify those wider patterns before Performance Agents assigns the response to an individual.
Contact-center AI has moved upstream to management
Observe.AI is entering a crowded part of the market. Level AI already says its software analyzes calls, emails and chats, generates personalized coaching plans and tracks performance. Cresta's Training Simulator builds practice scenarios from customer conversations, grades employees on defined behaviors and connects the results to coaching plans. Balto sells real-time guidance alongside coaching and quality software.
The agent label is table stakes. Observe.AI is selling the integration of conversation analysis, behavior detection, evidence gathering, plan preparation, manager approval and post-coaching measurement. Buyers will judge whether that loop produces reliable recommendations, fits existing operations and changes measurable performance without turning supervisors into passive reviewers of machine output.
Observe.AI says it serves more than 350 companies and has more than 300 employees. Jain leads Observe.AI alongside CTO and co-founder Jithendra Vepa, according to the company's current information page.
On April 12, 2022, Observe.AI raised a $125M Series C led by SoftBank Vision Fund 2, with Zoom participating, bringing disclosed funding to $213M. In that announcement, Observe.AI said the funding would support its effort to connect real-time and post-interaction coaching. Performance Agents delivers another piece of that strategy four years later, recast around agents that do the preparation while managers retain the decision.