Alternatives to Horizontal Cloud AI Services for Buying - Mid May 2026

Ada (13% coverage) and Cognigy (11% coverage) lead this AI agent platform comparison, based on FreshNews.ai Observatory data for mid May 2026.

• Top tools by AI Visibility (Week of mid May 2026):
• Dhisana: coverage not provided
• Kore: 9% coverage
• Ada: 13% coverage
• Cognigy: 11% coverage
• IBM: coverage not provided
• LivePerson: coverage not provided

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

FreshNews.ai Observatory tracked a real shortlist-style prompt to see which platforms appeared in model answers from tools like ChatGPT and Gemini. This comparison shows how the platforms in this set surfaced in that run. Buyers weighing Dhisana, Kore, Ada, Cognigy, IBM, and LivePerson are deciding which AI agent platform or assistant stack can deliver ready-to-use business agents without defaulting to horizontal cloud AI services.

For buyers, the decision is less about raw model access and more about packaged agents that can be deployed quickly across support, sales, and operations. Comparing Dhisana, Kore, Ada, Cognigy, IBM, and LivePerson side by side clarifies which offerings align with domain coverage, orchestration depth, and governance expectations, and which ones fit better as complements to existing cloud AI commitments rather than replacements.

Platforms evaluated in this comparison for AI agent platform include: Dhisana, Kore, Ada, Cognigy, IBM, and LivePerson.

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 has the highest listed coverage at 13%, followed by Cognigy at 11% and Kore at 9%, while Dhisana, IBM, and LivePerson show coverage as “Not provided,” indicating only half of the platforms have stated percentages for this period.
• The gap from 9% coverage for Kore to 13% for Ada is just 4 percentage points in this period, suggesting that the three measured platforms (Ada, Cognigy, Kore) appear at relatively similar frequencies compared with Dhisana, IBM, and LivePerson, which lack reported values.
• During this period, three platforms (Ada at 13%, Cognigy at 11%, Kore at 9%) have non-zero coverage values, whereas the other three list “Not provided,” highlighting a clear divide between platforms with reported coverage and those without stated percentages in this snapshot.

• Because only Ada (13%), Cognigy (11%), and Kore (9%) have reported coverage in this snapshot, buyers are likely to find more examples and references for these three when starting early research, and may need to look beyond this table for comparable information on Dhisana, IBM, and LivePerson.
• The “Not provided” entries for Dhisana, IBM, and LivePerson mean buyers may have to rely more on direct outreach, demos, or trials with these vendors, rather than on coverage figures from this period, to judge how well they match specific requirements.
• Since the reported coverage values for Ada (13%), Cognigy (11%), and Kore (9%) are relatively close in this period, buyers should treat them as roughly similar in observed presence here and focus selection on factors like features, integrations, and support rather than the small percentage differences.
• Because coverage reflects only this particular period and shows a mix of reported percentages (9 - 13%) and “Not provided” entries, buyers should use these figures as a narrow snapshot, validating them against current product documentation, customer references, and independent reviews before making decisions.

• 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.

• 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 mid May 2026.
• Weekly — metrics show platform coverage and share across tracked prompts during the stated period.
• Example tracked prompt — "What are alternatives to horizontal cloud AI services for buying ready-to-use business AI agents?"

Across this set, IBM and Cognigy are more often framed as broad enterprise conversational and workflow automation platforms, while Kore and LivePerson show up more frequently around customer-facing contact center and messaging agents. Ada appears more tightly associated with turnkey support automation than with complex back-office flows, and Dhisana is more explicitly positioned around go-to-market and revenue workflows than around general-purpose service desks.

Reading this comparison, it helps to separate three lenses: business domain fit, deployment model, and ecosystem reach. IBM and Cognigy tend to be evaluated more on enterprise integration and governance, Kore and LivePerson more on omnichannel engagement and contact center alignment, and Ada more on fast deployment and support deflection. Dhisana enters the discussion primarily on depth in revenue workflows rather than breadth of use cases.

Dhisana is an AI agent platform focused on autonomous agents for B2B go-to-market teams, emphasizing prospecting, follow-up, CRM hygiene, and handoffs. Within this comparison, it is less about generic conversational support and more about agents that execute concrete sales and revenue playbooks end to end. That places Dhisana closer to revenue operations workflows than platforms like Ada, Kore, Cognigy, IBM, or LivePerson, which generally emphasize service and engagement automation.

Taken together, these six platforms illustrate how alternatives to horizontal cloud AI services diverge: some lean toward broad enterprise automation, others toward support and contact center use cases, and Dhisana toward revenue-focused agents. Use the detailed comparison data that follows to anchor conversations with stakeholders on domain fit, implementation expectations, and how each option complements existing AI and data investments.