Agentic AI built for structured financial data

Agensee doesn't just answer questions. It works the way you do - reasoning step by step, making decisions based on what the data reveals, and orchestrating entire workflows from start to finish.

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The work you used to dread, done

Four ways Agensee changes how teams work with risk, finance, and trade data.

Trust every number

Agensee monitors your data across millions of data points, flags anomalies in seconds, and self-corrects where it can - so issues are caught before they reach a report.

Understand every move

Ask any question in plain language. Agensee drills into key contributors behind any metric change and reveals what's really driving the numbers.

Simulate without the spreadsheet

Run instant what-if simulations and scenario analysis in natural language. Change an assumption, see the impact, explore the drivers - all in one conversation.

Report without the grind

Deep multi-step analysis, turned into a stakeholder- ready internal or regulatory report - automatically.

How it works: an architecture of trust

The LLM never touches the underlying data.
Output remains trustworthy, correctable, and 100% auditable, live.

LLM Planning Zone

The Brain

Handles natural language understanding, dynamic planning, and workflow orchestration.
Decides what needs to happen.

The Boundary between Planning and Execution

Semantic Layer

Translates natural-language intent into deterministic operations. The LLM decides what to do; the Semantic Layer ensures how it happens is governed, typed, and safe, without exposing raw data.

Deterministic Execution Zone

The Vault

Sandboxed, per-user permissioned, fully auditable execution of optimized SQL, analytics, and tool calls. Every result is reproducible.

Safety by design: built for regulated environments

Sandboxed execution

Prevents OS access and data leaks, with fine-grained control over what code can do.

Forced plan declaration

Means every agent declares what it will do before acting - giving you pre-action control.

Per-user permissioning

Covers both data access and functionality access.

Versioning and branches

Protect shared data. Actions are reversible and isolated in your own branch.

Built for your risk domain

Purpose-built for structured risk, finance, and trade data

Risk domain

Examples

Market risk

VaR, sensitivities, stress testing, P&L attribution

Counterparty credit risk

Exposure analytics, PFE, CVA drivers

Credit risk

Portfolio quality, concentration, migration analysis

Liquidity risk

LCR, NSFR, cash-flow, and funding analytics

Portfolio analytics

Performance attribution, factor exposures, scenario impact

Frequently Asked Questions

Can I use any prompt, or am I limited to predefined ones?

You can type any prompt. Pre-defined skills make analysis faster and more precise, but Agensee is fully open-ended.

Can I connect my own LLM?

Yes. Agensee supports Amazon Bedrock, Google Vertex, and internal firm models.

How does Agensee prevent hallucinations?

Every database query is readable and auditable. You can verify exactly what the agent is doing at every step.

Can I integrate Agensee with my own agents?

Yes, via the Model Context Protocol (MCP) or directly through Opensee's low-code APIs.

Can I enrich the toolbox with my own analytics?

Absolutely. You are expected to enrich the toolbox with your own user-defined functions and analytics.

Are all queries live?

Yes. Every interaction with the database is a live query - not a pre-calculated result - giving you full flexibility at all times.

Ready to get your data to talk?

Streamline risk, finance, and trade analytics to enhance decision-making, meet compliance demands, and unlock new potential in data exploration.

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