Agentic Index
AgentOps vs Voker (2026)
Both vendors last verified
Both turn agent activity into something you can look at, for different audiences. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.
AgentOps is for engineers, with framework aware traces, an open source SDK and devtools for debugging production agents, free up to 5,000 events and Pro from $40 a month. Voker is the Amplitude for agents, a provider agnostic SDK turning conversations into structured analytics, automatically detecting intents, corrections and resolutions and tying agent behavior to business outcomes so whole product teams can measure agents without reading traces, free for 2,000 events a month, with paid plans from $80. Traces for the engineer against analytics for the product manager.
On the Agentic Index agent infrastructure ranking, neither AgentOps nor Voker clears the bar, which asks for all five production contract capabilities documented in full. AgentOps documents two of the five in full; Voker does not document security and identity governance in full, nor model flexibility and routing. 33 of the 186 vendors in the lane clear it. See the agent infrastructure ranking
This comparison is published by Agentic Index, an independent agentic AI vendor research platform. AgentOps and Voker 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 1,084 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded
Choose AgentOps if
- Debugging is the immediate job.
- Your users are engineers who will happily read a trace.
- Framework breadth matters because your agents are not all built the same way.
Choose Voker if
- Product managers need to see agent performance and nobody is going to read traces for them.
- Detecting corrections and resolutions automatically is the signal you actually want.
- Tying agent behavior to business outcomes is how you will justify continued investment.
| Feature | A AgentOps |
V Voker |
|---|---|---|
| Action & orchestration | ||
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Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
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AgentOpsIntegrations & Tool Calling The major agent frameworks and providers are instrumented natively, including AG2, Agno, CrewAI, the OpenAI Agents SDK, LangChain and LlamaIndex, and AgentOps traces the tool calls those agents make. These integrations bring trace data in, and none connects an agent to a real system to take actions. SourceAgentOps, docs.agentops.ai/llms.txt (integrations) and agentops.ai homepageread 2026-09-21 |
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VokerIntegrations & Tool Calling The SDKs wrap the OpenAI, Anthropic, Gemini and Vercel AI SDK clients and work with LangChain and CrewAI to capture a customer's agent calls and tool calls. A people API ties events to user data the customer already holds. These bring the customer's agent data into Voker. The agent calls its own tools, and Voker names no integration through which an agent reads or writes a real system. SourceVoker, docs.voker.ai overview, provider guides and people conceptread 2026-09-21 |
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Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
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AgentOpsWorkflow Orchestration Multi agent workflows the customer runs are visualized from their traces, with operations tied to named agents. AgentOps does not run workflows of its own, and nothing in it sequences, branches or retries steps or combines deterministic nodes with agent steps. SourceAgentOps, docs.agentops.ai/llms.txt (tracking agents, recording operations) and agentops.ai homepageread 2026-09-21 |
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VokerWorkflow Orchestration Customers build and run the agents Voker measures in their own code or in frameworks such as LangChain and CrewAI. Voker does not sequence, branch, retry or route agent steps. SourceVoker, docs.voker.ai overview and voker.ai homepageread 2026-09-21 |
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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. |
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AgentOpsTriggers & Channel Coverage When the customer's instrumented code runs, traces arrive and appear in the dashboard. AgentOps names no schedule, event trigger, alert or automation that starts work on its own. SourceAgentOps, docs.agentops.ai/llms.txt and agentops.ai homepageread 2026-09-21 |
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VokerTriggers & Channel Coverage Annotation runs automatically on every event Voker receives, tagging intents, corrections and resolutions. Voker also generates a Smart Skill for an agent on its own once it reaches a confidence threshold that the prompt is not handling a set of tasks, based on user corrections and logged errors. SourceVoker, docs.voker.ai auto annotations and Smart Skillsread 2026-09-21 |
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| Knowledge & context | ||
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Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
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AgentOpsKnowledge Grounding & RAG Calls a customer's agents make are traced, including retrieval steps where the customer instruments them. AgentOps names no document ingestion, index, retrieval layer or knowledge API that grounds an agent in company data. SourceAgentOps, docs.agentops.ai/llms.txtread 2026-09-21 |
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VokerKnowledge Grounding & RAG From their conversations, Voker identifies knowledge gaps in a customer's agents. It names no document ingestion, index, retrieval layer or knowledge API that grounds an agent in company data. SourceVoker, voker.ai homepage and docs.voker.ai overviewread 2026-09-21 |
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Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
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AgentOpsMemory & State Persistence Traces, sessions and completions are stored as records of the customer's agent runs. AgentOps names no session, workflow or long term memory that an agent reads and writes. SourceAgentOps, docs.agentops.ai/llms.txt (traces, core concepts)read 2026-09-21 |
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VokerMemory & State Persistence For analytics, Voker stores events, sessions and person profiles, and it tracks long running conversations as sessions. It names no session, workflow or long term memory that a customer's agent reads and writes through Voker. SourceVoker, docs.voker.ai events and sessions and long-running conversations cookbookread 2026-09-21 |
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| Control & trust | ||
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Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
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AgentOpsHuman Oversight & Guardrails Logs, errors and prompt injection attacks leave a data trail, and runs can be replayed for review. AgentOps names no approval step, consent checkpoint, runtime guardrail or pause and resume control over an agent's actions. SourceAgentOps, agentops.ai homepage and docs.agentops.ai/llms.txtread 2026-09-21 |
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VokerHuman Oversight & Guardrails Agents are measured after the fact, through annotations, rates and session summaries. Human reviewer settings decide whether Voker removes a Smart Skill without review. Voker names no approval step, checkpoint, guardrail or pause on the actions of the customer's agent. SourceVoker, docs.voker.ai Smart Skills and agent analyticsread 2026-09-21 |
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Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
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AgentOpsSecurity, Identity & Governance The Pro plan adds role based permissioning, and the Enterprise plan adds custom SSO, a custom data retention policy and on premise or self hosted deployment. Self hosting lets a customer apply its own security policies. The plans mention compliance standards, with no published report or auditor behind them. SourceAgentOps, agentops.ai homepage pricing section and docs.agentops.ai/v2/self-hosting/overviewread 2026-09-21 |
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VokerSecurity, Identity & Governance SSO comes with the Enterprise plan. Customers retain full ownership of their data, with custom retention on Enterprise. No security attestation is published. SourceVoker, voker.ai homepage and pricingread 2026-09-21 |
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Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
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AgentOpsObservability & Auditability Each agent run is recorded as a trace of spans for LLM calls, tool calls, operations and named agents, with the host environment captured automatically. The dashboard replays runs step by step with point in time precision, visualizes multi agent interactions and tracks tokens and cost. The Pro plan adds session and event export and unlimited log retention. A read only public API and an MCP server expose trace and span data. SourceAgentOps, docs.agentops.ai/llms.txt (traces, spans, host environment, public API, MCP server) and agentops.ai homepageread 2026-09-21 |
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VokerObservability & Auditability Every LLM call or wrapped execution becomes an event tied to an agent version and a person. Voker stores the ordered messages, including user inputs, system prompts and model responses, along with the agent's tool calls. Events group into sessions for a whole conversation or workflow, and teams drill from the dashboard into individual sessions to debug them. Data is kept 30 days on the free plan, 90 days on Starter, one year on Agent First and a custom period on Enterprise. SourceVoker, docs.voker.ai events and sessions, agent analytics, and voker.ai pricingread 2026-09-21 |
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Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
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AgentOpsDeployment & Data Residency Customers can use the hosted service or self host the whole platform (API server, dashboard, Supabase and ClickHouse data layers and an OpenTelemetry collector) on their own servers or cloud through Docker Compose, Kubernetes or deployment to AWS, GCP and Azure, so data stays on their own infrastructure. The Enterprise plan adds on premise deployment, self hosting on AWS, GCP and Azure, and a custom data retention policy. SourceAgentOps, docs.agentops.ai/v2/self-hosting/overview and agentops.ai homepage; docs.agentops.ai/v2/self-hosting/overview.mdread 2026-09-21 |
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VokerDeployment & Data Residency The platform is hosted, and self hosting is also available. The Enterprise plan includes self hosted deployment and custom data retention. SourceVoker, voker.ai homepage and pricingread 2026-09-21 |
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| Solution readiness | ||
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Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
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AgentOpsPrebuilt Agents, Templates & Packs Examples show how to instrument agents built with various frameworks, and AgentOps offers expert help building agents as a service. It names no ready made agents, templates or packaged workflows for customers to adopt. SourceAgentOps, agentops.ai homepage and docs.agentops.ai/llms.txt (examples)read 2026-09-21 |
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VokerPrebuilt Agents, Templates & Packs Cookbooks show how to instrument customer support and long running agents. Voker names no ready made agents, templates or packaged workflows a customer adopts for its own work. SourceVoker, docs.voker.ai cookbook overviewread 2026-09-21 |
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| Platform extensibility | ||
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Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
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AgentOpsModel Flexibility & Routing More than 400 LLMs and frameworks that a customer's agents call can be traced and costed, and tracing does not constrain which model the agent uses. Customers do not choose, route or key any model the product itself runs, and AgentOps names no model policy. SourceAgentOps, agentops.ai homepage and docs.agentops.ai/llms.txt (tracking LLM calls)read 2026-09-21 |
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VokerModel Flexibility & Routing Each agent version's model is recorded, and versions can be compared. The customer's code chooses and calls the model, and Voker offers no model selection, routing, fallback policy or provider configuration of its own. SourceVoker, docs.voker.ai overview and agents conceptread 2026-09-21 |
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APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
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AgentOpsAPIs, SDKs & MCP Extensibility AgentOps publishes open source Python and TypeScript SDKs with decorators, context managers and manual trace control, a read only HTTP public API for trace and span data, and an MCP server that exposes trace and span data to MCP clients, alongside an MCP docs server. SourceAgentOps, docs.agentops.ai/llms.txt (SDK reference, TypeScript SDK, public API, MCP server)read 2026-09-21 |
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VokerAPIs, SDKs & MCP Extensibility Python and TypeScript SDKs wrap the OpenAI, Anthropic, Gemini and Vercel AI SDK clients. For languages and frameworks the SDKs do not cover, a REST API with OpenAPI specs creates events, people, agents, agent versions and fingerprints. SourceVoker, docs.voker.ai Python SDK, TypeScript SDK and API referenceread 2026-09-21 |
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Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
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AgentOpsTesting, Debugging & Optimization Teams debug agents by rewinding and replaying runs with point in time precision, and a data trail of errors and prompt injection attempts is kept. AgentOps also offers fine tuning of specialized models on saved completions as an optimization step after deployment. It names no testing against fixtures or datasets, configurable quality gates or scoring of output quality over time. SourceAgentOps, agentops.ai homepage and docs.agentops.ai/llms.txtread 2026-09-21 |
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VokerTesting, Debugging & Optimization Each event is labeled with the user's intent, any correction and whether the intent was resolved. Voker reports resolution and correction rates per intent category and filters them by agent version, so teams compare how a prompt or model change affected each intent. Smart Skills generate prompt amendments from corrections and errors, flag skills that raise cost or correction rate, and version the agent each time. Teams compare those rates across versions to track quality over time and after each deployment. SourceVoker, docs.voker.ai categorization, auto annotations and Smart Skillsread 2026-09-21 |
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| Specialist automation | ||
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Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
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AgentOpsBrowser & Computer Use The product covers SDK instrumentation, tracing, the dashboard, a public API, an MCP server and self hosting. AgentOps names no browser, desktop or computer control by an agent. SourceAgentOps, docs.agentops.ai/llms.txtread 2026-09-21 |
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VokerBrowser & Computer Use The product covers analytics, annotations, Smart Skills and SDK instrumentation for AI agents, and Voker names no browser, desktop or computer control by an agent. SourceVoker, docs.voker.ai overview and llms.txtread 2026-09-21 |
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Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing | A AgentOps |
V Voker |
|---|---|---|
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Entry price Lowest public entry point |
Free up to 5,000 events · Pro from $40/mo · Enterprise custom | Free · paid from $80/month |
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Pricing confidence How public the numbers are |
Public, exact | Public, exact |
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Billing Primary billing axis |
usage | Monthly plans by event allowance, where an event is a user message, assistant message or tool call (about 15 per conversation on average); unlimited seats on every plan; Enterprise custom |
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Variable cost Workload / overage exposure |
Medium variable cost | High variable cost |
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Free tier / trial Try before you buy |
Free tier
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Free tier
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Buying motion Self-serve vs sales call |
Mixed | Mixed |
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Pricing verified When this pricing was last checked |
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