Data readiness and architecture

AI is only as good as the data it can reach.

We connect the systems your firm already runs on, clean and govern the data inside them, and build a foundation that reporting, AI assistants, and agents can trust, sized for a firm, not a Fortune 500 IT department.

Talk data with us Is our data ready?
A reference architecture for AI-ready dataSelect a stage to see what we build. Tool names are examples; we recommend what fits.
Swipe sideways to see the full diagram
Source systemsIngestionCloud data platformTransform and modelUse OrchestrationAirflow or built-in schedulers IngestionFivetran, APIs, CDC Cloud data platformSnowflake, Databricks, or Fabric RawTrustedKnowledge index dbt modelsTested, documented Reporting and BIPower BI, Looker AI assistants, agentsGrounded in your data Quality monitoringMonte Carlo or dbt tests Governance and security, across every layer GovernanceLift™ policies · role-based access · data classification · lineage · retention · audit trail
Data flowOrchestration and monitoring
For
The reality

Most AI projects stall on data, not on models.

The AI tools are ready. What usually isn't is the data behind them: client records split across practice management and billing, knowledge buried in document management systems, spreadsheets that only one person understands, and no agreement on what a number means.

An assistant that can't find the right document, or finds one it shouldn't, is worse than no assistant at all. In regulated firms, that second risk is the one that ends up in front of a client or a regulator.

Data readiness fixes both: the right data in reach, and the wrong data out of it.

Questions we hear first
Why do our reports never agree with each other?
Can AI search our documents without exposing privileged or patient data?
Do we really need a data warehouse at our size?
What happens to all this when our data person leaves?
Is your data ready?

Six signs your data will hold AI back.

If more than two of these sound familiar, start with data before you buy another AI tool.

The signWhat it breaksWhat we do about it
Reports disagree
Leadership stops trusting numbers, and AI repeats whichever version it finds first.
Shared definitions for key terms, built into tested data models.
Knowledge is trapped
AI can't answer questions about your own precedents, files, or history.
A governed knowledge index over your documents, respecting existing permissions.
Everyone can see everything
An assistant surfaces privileged, confidential, or patient data to the wrong person.
Data classification and access rules tied to your identity system.
Spreadsheets are the system
Critical processes depend on manual exports and one person's knowledge.
Automated ingestion and documented pipelines that survive staff changes.
No one knows it broke
Stale or missing data flows quietly into reports and AI answers.
Freshness and quality monitoring with alerts to a named owner.
No lineage
You can't explain to a client or auditor where an answer came from.
Lineage from source to report or AI answer, with an audit trail.
Sized to you

The right architecture depends on your size, not on what vendors sell.

The full reference architecture fits a larger firm or a portfolio. Many clients need less, and we will tell you so.

Getting started

Connected and clean

For firms that mainly need trustworthy reporting and a safe first AI assistant.

Existing Microsoft 365 or Google tools, a few managed connectors, a governed document index, and scheduled quality checks.
Growing

A single governed platform

For firms with several core systems, regular reporting needs, and multiple AI use cases.

A cloud data platform with raw and trusted layers, managed ingestion, dbt models, and role-based access.
Scaling

The full reference architecture

For larger firms, multi-entity groups, and PE portfolios standardizing across companies.

Everything above, plus orchestration, data quality monitoring, lineage, and agent workflows across systems.
How an engagement runs

From scattered systems to a foundation AI can use.

Select a phase to see what we do and what you walk away with.

Map what you have and how good it is.

We inventory your systems and data, profile quality in the sources that matter most, and trace how data moves today, including the spreadsheets and manual exports.

You walk away with: a system and data inventory, a data quality profile, and a readiness score for your priority AI use cases.
  • System and data source inventory
  • Data quality profiling
  • Current data flows, including manual ones
  • Access and classification review
  • Readiness score by use case
What you receive

A foundation you own and can explain.

Everything is documented, version-controlled, and handed over, whoever runs it next.

  1. Data readiness report

    Your systems, data quality, and readiness for each priority AI use case, scored.

    For leadership
  2. Target architecture

    A diagram and plan for the platform, pipelines, and governance your firm needs.

    For IT
  3. Data dictionary

    Shared definitions for clients, matters, revenue, and other key terms, with owners.

    For everyone
  4. Working pipelines and models

    Tested, documented code in your own repository and your own cloud account.

    For the data team
  5. Governance controls

    Classification, access rules, lineage, and audit trail aligned to GovernanceLift™.

    For compliance
Where this fits

Data readiness is what makes the rest possible.

Assess

AI assessment

Find out whether data is your biggest gap.

Explore assessments
Prepare

Data readiness and architecture

Connect, clean, and govern the data AI will use.

You are here
Govern

GovernanceLift™

Policies and oversight for how AI uses that data.

Explore governance
Build

Workflow orchestration & automation

Assistants and agents running on trusted data.

Explore automation
Why Vantara

We have run these systems, not just drawn them.

Practitioners in your systems

Our principals have run practice management, document management, HR, and identity systems as CIO, CTO, and CDO, including agent workflows connecting HR, directory, email, and collaboration platforms.

Governance from the first table

Privileged, confidential, and patient data are classified and protected before anything is indexed or shown to an AI tool.

Vendor-neutral and right-sized

We recommend the lightest architecture that meets your needs, and we disclose any vendor relationship.

Delivery capacity when you need it

Our onshore and offshore partners add engineering capacity for larger builds, under our oversight.

Get started

Three ways to begin.

Assessment3–4 weeks

Data readiness assessment

An inventory of your systems and data, a quality profile, and a readiness score for your top AI use cases, with a clear recommendation.

Request an assessment
Design4–6 weeks

Target architecture

A right-sized architecture, platform recommendations with costs, and a governance design your team can build from.

Discuss architecture
Build8–12 weeks

First use case, end to end

Pipelines, models, and a governed knowledge index for one high-value use case, live and monitored.

Discuss a build
Common questions

What firms ask us about data.

Have a question that isn't here? Call us at 347 674-1471.

Do we really need a data warehouse at our size?
Not always. If your needs are mainly reporting and a first AI assistant, a lighter setup built on tools you already license may be enough. We recommend a full data platform only when several systems, use cases, or entities make it pay off.
Which platform should we use?
It depends on your existing systems, skills, and budget. Firms heavily invested in Microsoft often fit Fabric well; others fit Snowflake or Databricks. We compare options on cost, security, and fit, and we don't take referral fees.
Can AI search our documents without exposing privileged or patient data?
Yes, if the index respects your existing permissions and sensitive data is classified first. We build the knowledge index so people, and AI acting for them, only see what they are already allowed to see.
Can our data stay in our own environment?
Yes. We build in your cloud account, under your security controls, and you own the code and configuration. Nothing is hosted by us unless you ask.
What does it cost to run?
Platform costs range widely with data volume and tools, from modest monthly subscriptions for a light setup to more for a full platform. The architecture design includes a running-cost estimate before you commit.

Get your data ready before you buy another AI tool.

Tell us which systems you run and what you want AI to do. We'll tell you plainly what stands in the way and the lightest way to fix it.

Talk data with usSee all services