Agentic Index

Avesha vs Resolve AI (2026)

Both run coordinated agent teams rather than a single agent, at 10.5 and 9 of 14. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.

Avesha's swarm monitors, diagnoses and remediates across Kubernetes and cloud, with root cause analysis, auto remediation and GPU orchestration. Resolve runs a multi agent parallel hypothesis team targeting eighty percent autonomous resolution, on a self learning knowledge graph with REST and MCP APIs. Avesha's GPU orchestration is the unusual inclusion: if your reliability problem and your GPU scheduling problem are the same problem, that is a real differentiator.

On the Agentic Index production ops ranking, neither Avesha nor Resolve AI clears the bar, which asks for all five resolution loop capabilities documented in full. Avesha does not document human oversight and guardrails in full; Resolve AI does not document observability and auditability in full, nor human oversight and guardrails. 10 of the 39 vendors in the lane clear it. See the production ops ranking

This comparison is published by Agentic Index, an independent agentic AI vendor research platform. Avesha and Resolve AI are each graded against the same 14 capability Agentic Index taxonomy, from the vendor's own public materials under the Agentic Index verification standard, alongside 969 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded

Choose Avesha if

  • Documented coverage is broader and GPU orchestration alongside reliability matches your estate.
  • Kubernetes and cloud together is the scope, and a swarm suits distributed diagnosis.
  • Auto remediation is the outcome, not a target percentage.

Choose Resolve AI if

  • Parallel hypothesis testing is the diagnostic method you find most credible.
  • A self learning knowledge graph compounds value across incidents.
  • MCP APIs mean your other agents can reach the incident context.
At a glance Avesha Resolve AI
Category SRE / DevOps agent SRE / DevOps agent
Entry price Enterprise pricing; not publicly listed Contact sales; enterprise contracts, no public rates
Free / trial Credentials are provisioned through Avesha; no public self serve tier. Enterprise evaluations and proofs of value through sales; no self serve trial
Pricing confidence contact only contact only
Feature
A
Avesha
R
Resolve AI
Action & orchestration

Integrations & Tool Calling

Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools.

Full / Explicit Full / Explicit

Workflow Orchestration

Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps.

Full / Explicit Full / Explicit

Triggers & Channel Coverage

How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools.

Full / Explicit Full / Explicit
Knowledge & context

Knowledge Grounding & RAG

Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers.

Full / Explicit Full / Explicit

Memory & State Persistence

Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer.

Full / Explicit Partial
Control & trust

Human Oversight & Guardrails

Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls.

Partial Partial

Security, Identity & Governance

RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy.

Partial Full / Explicit

Observability & Auditability

Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior.

Full / Explicit Partial

Deployment & Data Residency

Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting.

Full / Explicit Partial
Solution readiness

Prebuilt Agents, Templates & Packs

Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value.

Full / Explicit Full / Explicit
Platform extensibility

Model Flexibility & Routing

Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys.

No / Not documented No / Not documented

APIs, SDKs & MCP Extensibility

Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems.

Full / Explicit Full / Explicit

Testing, Debugging & Optimization

Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment.

Partial No / Not documented
Specialist automation

Browser & Computer Use

Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone.

No / Not documented No / Not documented

Pricing snapshot

Sourced from the Index pricing dataset · open each vendor's profile for full detail.

Pricing
A
Avesha
R
Resolve AI

Entry price

Lowest public entry point

Enterprise pricing; not publicly listed Contact sales; enterprise contracts, no public rates

Pricing confidence

How public the numbers are

Contact only Contact only

Billing

Primary billing axis

Enterprise engagements scoped to environment size and workloads; self hosted install with provisioned credentials. enterprise contract

Variable cost

Workload / overage exposure

High variable cost Low variable cost

Free tier / trial

Try before you buy

No free tier
No free tierTrial

Buying motion

Self-serve vs sales call

Sales call Sales call

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