How much does Opensee cost?

Enterprise pricing that is not publicly listed and is arranged directly or via AWS Marketplace, typically scoped to data volume and deployment.

What are the best alternatives to Opensee?

Based on documented capability coverage across the Agentic Index 14 point taxonomy, the closest alternatives to Opensee among data analyst agents are Kaaj AI, Pluvo, Potato, Prophet. Each is graded on the same public evidence, and no vendor pays for placement.

Does Opensee give you tracing and observability into agent runs?

Full under the Agentic Index verification standard. Opensee publishes public evidence of tracing, observability and audit logging into agent runs, so a team can see what an agent did and why. Evidence basis: agent actions are auditable with traceability suited to regulated finance (opensee.io). Graded from public evidence only against the Agentic Index 14 point capability taxonomy. No vendor pays for placement.

Does Opensee require human approval before an agent acts?

Full under the Agentic Index verification standard. Opensee publishes public evidence of human approval steps and guardrails, so an agent action can be held for review before it executes. Evidence basis: agents declare actions before execution, run within permissions and guardrails, and support reversible actions in branches (opensee.io). Graded from public evidence only against the Agentic Index 14 point capability taxonomy. No vendor pays for placement.

Can you bring your own model or route between providers with Opensee?

Full under the Agentic Index verification standard. Opensee publishes public evidence of bring your own model and bring your own key (BYOK), and of routing tasks between models or providers rather than being locked to one. Evidence basis: supports multiple model backends including Amazon Bedrock, Google Vertex, and internal models (opensee.io). Graded from public evidence only against the Agentic Index 14 point capability taxonomy. No vendor pays for placement.

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Opensee

Q: Who is Opensee for?

Banks and financial institutions, Hedge funds and asset managers, Risk and finance data teams

Also known as: Agensee

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Data analyst agentprivateVerified 2026-07-09

Entry priceEnterprise pricing via AWS Marketplace or direct; not publicly listedFull pricing detail

Agentic analytics for financial risk and trading data whose multi agent system autonomously queries, analyzes, and acts on real time big data within permissions and guardrails.

Opensee provides real time big data analytics for financial risk and trading, and its Agensee layer adds an agentic AI system for the domain. A multi agent design pairs an orchestrator with a query manager and a data analyzer that plan and execute multi step analysis autonomously, translating natural language into queries over the firm's own data. Agents share context and memory, declare actions before executing, run sandboxed and permissioned, and support reversible actions in branches so analysts stay in control. The system supports multiple model backends including Amazon Bedrock, Google Vertex, and internal models, and user defined functions extend it. Opensee is used by financial institutions and hedge funds such as Taula Capital, is available through AWS Marketplace, and has been recognized by Chartis in its RiskTech AI 50 for use of AI on risk data across two consecutive years. The company has raised a Series A.

Vendor details

Canonical URL

https://www.opensee.io

Funding status

Series A

Company status

private

Use cases & customers

Primary use cases

Natural language analytics on risk and trading dataAutonomous multi step data analysisReal time big data explorationGoverned and auditable agent actions in finance

Target customers

Banks and financial institutionsHedge funds and asset managersRisk and finance data teams

Deployment options

AWS MarketplaceCustomer data environment

Integrations

Agents invoke SQL, analytics functions, and tools over the customer's real time data; available via AWS Marketplace with support for Amazon Bedrock, Google Vertex, and internal model backends; user defined functions extend the system.

Sources & related URLs

Research sources

https://www.opensee.io/

Agentic Index coverage score

10.0 / 14 capabilities · 71%

Integrations & Tool Callingagents autonomously invoke SQL, analytics functions, and tools, with connectors into the data platform and the AWS ecosystem (opensee.io, aws marketplace)	Full
Workflow Orchestrationan Orchestrator agent coordinates Query Manager and Data Analyzer agents to execute multi step analytics autonomously (opensee.io)	Full
Knowledge Grounding & RAGnatural language querying is grounded in the customer's real time financial and risk data (opensee.io)	Full
Human Oversight & Guardrailsagents declare actions before execution, run within permissions and guardrails, and support reversible actions in branches (opensee.io)	Full
Security, Identity & Governanceagents run sandboxed, permissioned, and auditable for financial data; specific certifications are not detailed in reviewed sources (opensee.io)	Partial
Observability & Auditabilityagent actions are auditable with traceability suited to regulated finance (opensee.io)	Full
Memory & State Persistenceagents share context and memory across a session to coordinate analysis (opensee.io)	Full
Deployment & Data Residencyavailable via AWS Marketplace and deployable in the customer's data environment; full residency options are not detailed (aws marketplace, opensee.io)	Partial
Prebuilt Agents / Templates / Packsships with orchestrator, query manager, and data analyzer agents plus user defined functions (opensee.io)	Partial
Triggers & Channel Coverageagents are triggered by natural language queries over real time data; broader event triggers are not detailed (opensee.io)	Partial
Model Flexibility & Routingsupports multiple model backends including Amazon Bedrock, Google Vertex, and internal models (opensee.io)	Full
APIs / SDKs / MCP Extensibilityuser defined functions and platform APIs extend the system; MCP is not documented (opensee.io)	Partial
Testing, Debugging & Optimizationreversible actions in branches and pre action declaration allow safe testing of agent actions; a formal evaluation framework is not detailed (opensee.io)	Partial
Browser / Computer-useno browser or computer use capability documented (opensee.io)	Unable to verify

The Agentic Index coverage score grades every vendor Full, Partial or Unable to verify against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded

Pricing

Enterprise pricing via AWS Marketplace or direct; not publicly listed

Enterprise engagements scoped to data volume and deployment; available via AWS Marketplace or direct.

Cost watchouts

Data scale, compute, and deployment model drive cost; no public rate is available.

Variable cost rationale

Cost scales with data volume, compute, and deployment scope in the customer environment; no public rate is available.

Sales call required

Yes, required for paid access

Free / trial

No free tier or trial documented.

Lowest paid plan

Not publicly listed.

Key ambiguities

No public pricing; enterprise engagements are scoped to data scale and deployment model.

Agentic Index verified 2026-07-09

Official pricing page

Related vendors

Alternatives to Opensee

The closest documented capability profiles to Opensee among data analyst agents tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.

Kaaj AI10.0 / 14Fuller documented coverage on Security, Identity & Governance and Triggers & Channel Coverage
Pluvo9.0 / 14Fuller documented coverage on Triggers & Channel Coverage
Potato10.0 / 14Fuller documented coverage on APIs, SDKs & MCP Extensibility and Testing, Debugging & Optimization
Prophet8.0 / 14A lighter documented profile than Opensee
Zenlytic10.0 / 14Fuller documented coverage on Security, Identity & Governance and Triggers & Channel Coverage
Wobby8.5 / 14Fuller documented coverage on Triggers & Channel Coverage

Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded

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Data confidence: high

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