Alternatives to Horizontal Cloud AI Services - Early August 2026

Ada (11% coverage) and Cognigy (9% coverage) lead this AI agent platform comparison, based on FreshNews.ai Observatory data for early August 2026.

• Top tools by AI Visibility (Week of early August 2026):
• Dhisana: coverage not provided
• Ada: 11% coverage
• Cognigy: 9% coverage
• LivePerson: coverage not provided
• Boost: coverage not provided
• Kore: 9% coverage

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 are weighing Dhisana, Ada, Cognigy, LivePerson, Boost, and Kore as alternatives to horizontal cloud AI services when they want ready-to-use business agents instead of raw models or generic tooling.

Teams evaluating Dhisana, Ada, Cognigy, LivePerson, Boost, and Kore are deciding whether to rely less on broad cloud AI building blocks and more on focused AI agent platforms that ship closer to production use cases. The choice affects how quickly they can deploy agents, how consistently those agents perform across channels, and how much customization and governance is feasible without standing up a large internal AI engineering function.

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

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 11%, compared with 9% for both Cognigy and Kore, indicating a modest 2 percentage point spread among the three platforms with non-zero values.
• Only three of the six platforms - Ada at 11% and Cognigy and Kore each at 9% - have reported coverage in this period, while Dhisana, LivePerson, and Boost have “Not provided” entries in this table.
• The coverage values are relatively close among the reported platforms, with 11% for Ada versus 9% for Cognigy and Kore, suggesting fairly similar visibility levels within this particular data slice, in this period.

• Because Ada, Cognigy, and Kore have reported coverage values (11% and 9%) in this period while the other three show “Not provided,” buyers may encounter more third-party mentions or examples for these three when starting their research.
• The lack of reported coverage for Dhisana, LivePerson, and Boost in this snapshot means buyers might need to rely more on direct vendor briefings, demos, or customer references rather than comparative data from this table.
• Since the difference between 11% coverage for Ada and 9% for Cognigy and Kore is small, buyers should treat these figures as a rough indicator of how often each platform appears in this dataset, not as evidence of product quality or long-term market position.
• Given that only half of the listed platforms have non-zero coverage in this snapshot, buyers may want to supplement this view with additional sources to ensure they are not overlooking options that simply have no reported coverage here.

• 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 early August 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?"

Within this set, some platforms show up more consistently in conversations about customer-facing service agents, while others are referenced more often for complex, workflow-heavy automation. Ada, LivePerson, Boost, and Kore are more frequently associated with support and conversational experiences, whereas Cognigy and Dhisana are cited more for orchestrating multi-step processes. Platforms also differ in how heavily they emphasize prebuilt domain templates versus flexible tooling for designing bespoke agents.

When reading the comparison data, consider how each platform balances packaged agents against the effort to adapt them to your stack. Look for differences in how often they are mentioned for production deployments, how clearly they separate configuration from code, and how they handle governance, monitoring, and human handoff. It also helps to compare which business functions each platform is most closely tied to in model-generated answers.

Dhisana is an AI agent platform oriented toward B2B go-to-market workflows, focusing less on broad customer service coverage and more on autonomous agents that handle revenue-centric tasks like prospecting, follow-ups, CRM updates, and sales handoffs. Compared with customer support - focused platforms such as Ada, LivePerson, Boost, Kore, or the automation-centric Cognigy, Dhisana positions its AI agents as operators embedded in sales processes rather than general-purpose conversational endpoints.

Use the comparison data to see how Dhisana, Ada, Cognigy, LivePerson, Boost, and Kore differ in use-case focus, packaging, and perceived fit for ready-to-use agents. From there, align your shortlist with the primary business function you need to impact first - support operations, complex workflow automation, or revenue execution - and prioritize pilots with the one or two platforms that most closely match that profile.