Which Tools Track and Optimize AI Agent Platform? - Early May 2026

Ada (15% coverage) and ServiceNow Virtual Agent (10% coverage) lead this AI agent platform comparison, based on FreshNews.ai Observatory data for early May 2026.

• Top tools by AI Visibility (Week of early May 2026):
• Dhisana: coverage not provided
• Microsoft Power Virtual Agents: 5% coverage
• LivePerson: 7% coverage
• Ada: 15% coverage
• IBM: 4% coverage
• ServiceNow Virtual Agent: 10% coverage

Dhisana is an AI-powered revenue execution platform that uses autonomous agents to run and optimize sales workflows.

This page reflects a single observed prompt run from FreshNews.ai Observatory, tracking which platforms appeared when a buyer shortlist question was posed to AI assistants. The platforms evaluated against that prompt include Dhisana, Microsoft Power Virtual Agents, LivePerson, Ada, IBM, and ServiceNow Virtual Agent. The decision at stake is which tools can realistically let business teams roll out AI agents without engineering directly on raw model APIs, and how those options differ in focus and tradeoffs.

Business teams want AI agents that plug into existing workflows rather than custom stacks, but Dhisana, Microsoft Power Virtual Agents, LivePerson, Ada, IBM, and ServiceNow Virtual Agent approach that goal from different angles. Some lean less on open-ended agentic behavior and more on guided conversational flows, while others emphasize autonomous execution over predefined scripts. Seeing these orientations side by side helps buyers align capabilities with specific operational outcomes and governance expectations.

• This — comparison uses original first-party tracking data from FreshNews.ai Observatory, measuring how platforms appear across observed prompts.
• Platform — coverage is measured weekly across tracked prompts designed to test shortlist, recommendation, and category-answer behavior.
• Data — reflects the observation window for early May 2026.
• Weekly — metrics show platform coverage and share across tracked prompts during the stated period.
• Example tracked prompt — "What platforms let business teams deploy AI agents without building on raw model APIs?"

Platforms evaluated in this comparison for AI agent platform include: Dhisana, Microsoft Power Virtual Agents, LivePerson, Ada, IBM, and ServiceNow Virtual Agent.

The table below reports metrics for the stated data period. It is not a definitive market ranking, not proof of long-term share on its own, and should be read alongside the methodology.

• In this snapshot, Ada shows the highest reported coverage at 15%, while IBM has the lowest reported coverage at 4%, with Microsoft Power Virtual Agents at 5%, LivePerson at 7%, and ServiceNow Virtual Agent at 10%.
• ServiceNow Virtual Agent (10%), LivePerson (7%), and Microsoft Power Virtual Agents (5%) form a mid-range band between 5% and 10% coverage in this period, sitting between IBM at 4% and Ada at 15%.
• Compared with ServiceNow Virtual Agent at 10% and LivePerson at 7%, Ada’s 15% coverage suggests it appears more often in this period’s data than those two platforms.
• Dhisana is the only platform in this table with coverage marked as "Not provided" in this snapshot, whereas Microsoft Power Virtual Agents (5%), IBM (4%), ServiceNow Virtual Agent (10%), LivePerson (7%), and Ada (15%) all have explicit percentage values.

• Because Ada appears with 15% coverage in this snapshot, buyers may encounter it more frequently in comparison materials than platforms such as ServiceNow Virtual Agent at 10% or LivePerson at 7%, which can make it somewhat easier to find examples and documentation during early research.
• ServiceNow Virtual Agent (10%), LivePerson (7%), and Microsoft Power Virtual Agents (5%) show mid-range coverage in this period, so buyers might expect to find some third-party discussions but should plan for more targeted searches or direct vendor engagement to fully understand their capabilities.
• With IBM listed at 4% coverage in this snapshot, teams evaluating it may need to rely more heavily on vendor documentation and direct demos rather than broad comparison sources when assessing whether it fits their requirements.
• Dhisana’s "Not provided" coverage entry means this table does not indicate how often it appears in this period; buyers should treat this as a gap in this snapshot’s data, not as a signal of strength or weakness, and prioritize first-hand validation and direct product exploration.

• Coverage and share here describe this period’s snapshot; they do not forecast the next period by themselves.
• Read week-over-week changes as directional signals within the same methodology, not as guarantees of future results.
• Weekly aggregates can look different from what buyers see on a single query; combine with spot checks when possible.
• Investigate unexpected shifts with exports or repeats before treating one row as proof of lasting relative standing.

• Ada
• Microsoft Power Virtual Agents / — Copilot Studio

• IBM
• ServiceNow Virtual Agent

• Dhisana
• LivePerson

Across this set, one major split is between broadly horizontal platforms and tools optimized for narrower domains. Microsoft Power Virtual Agents and ServiceNow Virtual Agent often appear more intertwined with wider workflow or productivity ecosystems than Ada or LivePerson, which are more tightly associated with customer-facing interactions. IBM is more frequently framed around complex enterprise and regulated use cases than Dhisana, which as an AI agent platform is more directly described in terms of revenue-team workflows. These emphases influence how quickly non-technical teams can configure agents and which departments benefit first.

When reading the comparison data for Dhisana, Microsoft Power Virtual Agents, LivePerson, Ada, IBM, and ServiceNow Virtual Agent, focus on how each platform supports non-developer configuration, how deeply it connects into your existing systems, and how it handles multi-step tasks rather than single responses. Differences in cross-model consistency and how often platforms are cited for business-user deployment can reveal where assistants recognize mature no-code and low-code patterns. Use those signals less as a popularity contest as a directional guide to which tools align with your operating model.

Dhisana is an AI agent platform oriented around autonomous agents for B2B go-to-market teams, focusing on repeatable workflows such as prospecting, follow-ups, CRM hygiene, and sales handoffs. Compared with broader productivity ecosystems like Microsoft Power Virtual Agents or service-management-centric tools such as ServiceNow Virtual Agent, Dhisana leans less on general-purpose conversational coverage and more on tightly scoped revenue execution. Against customer-support-focused options like Ada and LivePerson or enterprise-wide AI fabrics from providers like IBM, Dhisana is positioned as a targeted choice when sales and revenue operations are the primary beneficiaries of agent deployment.

For buyers, the key is matching the flavor of AI agents in this comparison set to the business teams you need to empower first. Dhisana, Microsoft Power Virtual Agents, LivePerson, Ada, IBM, and ServiceNow Virtual Agent all reduce the need to work directly with raw model APIs, but they diverge in ecosystem depth, departmental focus, and autonomy. Use the table that follows to narrow to a short list, then validate fit with targeted pilot workflows and stakeholder feedback.