AI agent data integration for financial institutions

Connect your AI agents to data they can be trusted with.

IData designs, deploys, and operates agent data workflows on Datris, the open-source data control plane we built. Governed access, validated feeds, and a full evidence trail, inside your infrastructure.

Founded in 1998. Building on AWS since 2007. Mission-critical data infrastructure for pension funds, prime brokerages, asset managers, and government-sponsored enterprises.

1998 Founded. Financial services from day one.
$200B+ Assets under management at our largest client engagement
Fortune 500 Clients across banking, asset management, and pensions
70+ Agent tools in Datris, the open-source platform we maintain

"The agent prototype works. The path to production data does not. Nobody can say which data the agent may read, whether that data was checked, or what the agent did with it. We build that path."


Why agents stall at the data layer

🔒

Ungoverned access

The agent gets a service account and a connection string. Security asks what it can reach. Nobody has a precise answer.

🧾

No evidence trail

When an answer is wrong, there is no record of which feed, which version, or which rule it came from. Compliance cannot sign off on that.

🧩

Hand-built, fragile feeds

Each source gets a one-off script. Vendors change formats, schemas drift, and the people who wrote the scripts move on.


Assess. Implement. Run With You.

Three stages, each priced and scoped on its own. Start with one workflow. Every engagement reuses the connectors, policies, and patterns from the last, so the second workflow costs less than the first.

Assess

Agent Data Assessment

Fixed fee · 2–3 weeks

We pick one agent workflow with you, confirm data rights and access, baseline the manual effort it replaces, and define what "done" means.

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Implement

Agent Data Integration

Fixed scope · 6–10 weeks

We connect the agreed sources to your agent through Datris, inside your infrastructure, with validation, access policy, audit, and lineage switched on from day one.

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Operate

Run With You

Recurring · in your infrastructure

We stay accountable for the integrations we built. Source changes, failures, upgrades, and expansion, handled inside your perimeter under your access controls.

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Investment research data for an AI agent

A research team has an agent that answers questions well in a demo. To use it for real, it needs approved vendor data, selected internal research, and portfolio positions, with every record validated and every access recorded. This is what we build.

How an agent data workflow runs on Datris Approved sources flow into Datris, where they are acquired, validated, governed by policy, and recorded with provenance, then published to the research agent and to the lake or warehouse. APPROVED SOURCES DATRIS · YOUR INFRASTRUCTURE CONSUMERS Market data vendors files · APIs · feeds Filings and documents PDF · HTML · email Internal research notes · models · tables Portfolio systems databases · warehouses Data control plane Acquire on schedule or on event Validate every record Enforce access policy Record provenance and lineage audit log · secrets · field protection Research agent via MCP · governed tools Lake or warehouse Databricks · Snowflake · Iceberg same lineage, both sides
One workflow, end to end. Datris sits beside your lake and warehouse, loading and governing. It does not replace them.

Acquire and validate

Datris taps pull each source on a schedule or on event. Validation rules, written in plain language and enforced on every record, stop bad data before the agent sees it.

Govern the agent

The agent reaches data only through governed tools. Policy decides what it may read and do. Sensitive fields are protected before they leave the platform.

Prove what happened

Every run has lineage and an audit entry: which source, which version, which rule, which agent. Compliance can trace any answer back to the data that produced it.


Delivered by the people who built the platform

🔍

Open source, inspectable

Datris is open source. Your security team can read every line, your platform team can fork it, and nothing phones home. datris.ai →

🏛️

Runs inside your perimeter

Your cloud or your data center, your credentials, your access controls. We work within them. There is no hosted service and no third-party processor.

🏦

Financial services since 1998

Pension funds, prime brokerages, asset managers, and government-sponsored enterprises. We know the data, the controls, and the review process.

♻️

Reuse, not rebuild

Taps, policies, destination patterns, and acceptance suites carry from one engagement to the next. You pay for your workflow, not for us to start over.

AI Platforms
OpenAIAnthropicAWS BedrockAzure OpenAIGoogle Vertex AI
Cloud & Data
AWSAzureGCPDatabricksTerraform
Agent & Platform
DatrisModel Context ProtocolApache SparkApache KafkaHashiCorp Vault
Lake & Warehouse
Databricks Unity CatalogSnowflakeApache IcebergPostgreSQLMongoDB

Proven Results

Enterprise Data Lake for a $200B Pension Fund

Built a cloud-based data ecosystem that gave investment teams instant, governed access to hundreds of datasets. The foundation that agent workflows now build on.

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AI-Powered OpsChat for Enterprise Operations

A conversational interface that lets support staff diagnose operational issues instantly, ingesting 140,000+ log messages per second into governed retrieval.

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Datris: the platform behind the work

The open-source data control plane we created and maintain. Agents operate pipelines through governed tools, with policy, lineage, and audit built in.

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Latest Thinking

Start with one workflow.

Request a proposal →
  • UBS
  • Goldman Sachs
  • Credit Suisse
  • Bank of America
  • Deutsche Bank
  • CPP Investment Board
  • Freddie Mac