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 for acquiring ready-to-use business AI agents that can operate reliably in production.

Choosing among these AI agent platforms is less about raw model access and more about how quickly teams can deploy working agents into real customer or revenue workflows. Ada, Cognigy, LivePerson, Boost, Kore, and Dhisana all promise faster time-to-value, but they differ in maturity around enterprise integrations, guardrails, and how much configuration a business user can handle without leaning heavily on central engineering.

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.

• Ada shows 11% coverage in this snapshot, appearing slightly more often than Cognigy and Kore, which are both listed at 9%.
• Cognigy and Kore share the same reported coverage at 9%, indicating similar representation in this period among platforms with available percentages.
• Dhisana, LivePerson, and Boost all have coverage marked as not provided, so this snapshot does not offer a numerical comparison between them and Ada at 11% or Cognigy and Kore at 9%.
• The small 2-point gap between Ada at 11% and Cognigy and Kore at 9% suggests only a modest coverage difference among platforms with reported values in this period.

• Because Ada is listed at 11% coverage versus 9% for Cognigy and Kore in this period, buyers may notice Ada slightly more often in sources that mirror this snapshot, but the difference is modest and should not replace detailed evaluation.
• The matching 9% coverage for Cognigy and Kore suggests buyers can treat their apparent presence in this dataset as similar and instead focus on differences in features, integrations, and support when comparing them.
• With coverage shown as not provided for Dhisana, LivePerson, and Boost, buyers should not infer weaker or stronger performance from this table alone and may need to rely more on demos, trials, and references for those platforms.
• Given the narrow spread between 11% and 9% coverage among platforms with reported values, buyers should treat these percentages as a directional signal of visibility in this snapshot, not as a definitive ranking of quality or long-term adoption.

• 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?"

Across the set, Ada, LivePerson, Boost, and Kore are more commonly positioned around customer-facing support and engagement, while Cognigy and Dhisana appear more frequently in conversations about complex, workflow-centric automation. Some platforms skew more toward low-code, visual builders, whereas others emphasize reusable components and deeper back-end orchestration. Visibility patterns also differ: certain names show up more often accurately across multiple assistants, while others are mentioned more sporadically or in narrower contexts.

When reading the comparison data, focus first on whether each platform is oriented toward customer service, sales and revenue workflows, or broader enterprise automation. Then look at how consistently each vendor is referenced across AI assistants, which can hint at how well their positioning is understood. Finally, compare the balance between ready-made, domain-specific agents and flexible frameworks that let you design agents tailored to your own processes.

Dhisana is an AI agent platform centered on autonomous agents for B2B go-to-market teams, focusing less on general-purpose customer support and more on specialized sales and revenue workflows such as prospecting, follow-ups, CRM hygiene, and qualified handoffs. Compared with Ada, Cognigy, LivePerson, Boost, and Kore, Dhisana concentrates more tightly on repeatable revenue execution, offering agents designed to work alongside existing GTM stacks rather than spanning a broad range of generic interaction scenarios.

For buyers moving beyond horizontal cloud AI services, this set highlights a spectrum from customer-service - oriented platforms (Ada, LivePerson, Boost, Kore) to workflow-heavy automation options (Cognigy, Dhisana). Use the comparison to align stakeholders on which domains matter most, then narrow in on the platforms whose agent templates, orchestration depth, and ecosystem integrations best match your immediate business workflows.