Introducing Strata

The AI foundation that knows your business.

Strata connects your data, documents, and agreed business definitions into one governed layer, then brings everyday AI to every employee and gives your agents the context to finish real work.

Knowledge · AI · Deployed · Enabled

Ask the question. Get a sourced answer. Finish the work.

Employees get sourced answers in seconds. AI agents get the context and permissions to finish workflows end to end.

Your question

Why are configured quotes taking longer to turn around this quarter, and what should we change?

CFO of a PE-owned manufacturing company

Company context

Quote cycle timesERP

“Quote turnaround” definitionSemantic layer

Engineering change logSharePoint

Discount guardrail decisionMemory

Answer and action

[Finding, in company terms, with a citation to each source used.]

4 sources cited Approved definition used

Routing change drafted, waiting for your review

Illustrative example.

The problem

AI value plateaus at chat until context, skills, and agents unlock it.

Most companies have licenses, a usage policy, and some training. The tools still know nothing about the business, so answers stay generic and the work still gets finished by hand.

1. Pockets of usage

Personal or free tools, no policy. Gains are invisible and carry data risk.

2. Enablement

Licenses, policy, and training. Tools still know nothing about the business.

3. Chat adoption

Weekly drafting and research. Generic answers; workflows finished by hand.

4. Skill sharing

Tasks that work become repeatable skills shared across teams.

5. Context layer

Ontology, standards, and data, unified and governed. Valid answers in company terms.

6. Agent Studio

Employees set up, schedule, and share agents. Work done end to end with human review.

Stages 1 to 3: the chat plateau. Stages 4 to 6: where value compounds, and where Strata does its work.

Introducing Strata

One governed foundation, built in layers.

Each layer depends on the one beneath it. Value shows up at the top, and it is only as good as the foundation below.

People, agents, and workflows

Employees get sourced answers. Agents finish workflows with the right context and permissions.

Access

Company context everywhere: AI chat in Claude, ChatGPT, or your own app, enterprise search, and APIs and MCP for agents.

Retrieval and context

Finds the right facts and hands them over with citations.

Knowledge layer

Business definitions: an entity graph for customers, products, contracts, and people, and how they relate.

Unified data catalog: every structured and unstructured source, indexed, classified, and linked to its owner.

Memory: past decisions, their rationale, and agent history.

Connectors and ingestion

Syncs, cleans, deduplicates, and tags every source.

Sources

Structured: ERP, CRM, HRIS, billing, finance, and the data warehouse. Unstructured: SharePoint and drives, email, Slack and Teams, tickets, wikis, and call transcripts.

Governance wraps every layer

Explicit opt-in for each source

Permissions inherited from each source

Lineage and citations on every answer

Quality and freshness checks

PII and policy controls

Audit log of every query and agent action

Where Strata fits

Everyday AI for everyone. Purpose-built solutions where it counts.

Sales · Finance · Operations · Supply chain · HR · Legal

The same assistant for everyone

It already knows the company’s language, metrics, and how the work actually gets done, because it reads from Strata. No separate model stack.

Morning briefing and to-dos Email and document drafting Meeting notes and follow-ups Research and summarization “How do we do X?” answers Self-serve analytics Deck and memo generation Policy and process lookup

Use cases

Start with the workflows worth the most.

A small number of high-value, end-to-end workflows, pursued in a logical sequence so each one builds on the foundation the last one laid.

Quote → BOM automation

Configured quotes, bills of material, and order entry.

Pricing

Elasticity, price setting, and discount guardrails.

Inventory and demand planning

Forecasting, stocking levels, and supplier signals.

Dealer lead generation and support

Lead routing, enablement, and service answers.

Self-serve answers and analysis

Prompting, skills, and enablement for every team.

Next: multi-agent applications

Teams of agents that build and run end-to-end workflows on the same foundation.

Revenue generation Finance CoE Manufacturing execution Patient management

Where Strata sits in your stack

Keep your systems of record. Add the layer AI has been missing.

Layer	What we see in market	Recommended path
Multi-agent applications	Emerging fast, mostly pilots. Few in production.	Build on the company brain for priority use cases.
Personal enablement and use cases	Many “toss it over the fence” rollouts. Named opportunities, inconsistent deployment.	Roll out on the company brain with stronger governance. Pursue high-value use cases in sequence.
Company brain (Strata)	Nascent. Basic MCP connections typically in place.	Deeper access to accumulated company knowledge, with governance built in.
Data layer	Structured data often weak. Unstructured data is critical to AI.	Cleanse and conform structured data into a unified model. Connect unstructured data to the company brain.
Packaged applications	ERP, CRM, HCM, and finance will endure, but are losing relevance.	Maintain as systems of record. Limit new investment where possible.

How we deliver

Knowledge. AI. Deployed. Enabled.

Strata is a platform and a team. We’ve been operators, so we stay engaged until the value is real.

Knowledge

Connect your sources, agree the definitions, and capture the decisions and history your team relies on.

AI

Put assistants, skills, and agents on that foundation, so answers come back in your company’s terms.

Deployed

Our team stands Strata up and ships the first high-value workflows into production, not another pilot.

Enabled

Role-based training and enablement labs, so every employee uses it and good work spreads across teams.

Built for your priorities

Move the business forward. Keep control of how.

CEOs and operating partners

Steer with the full picture.

Ask the strategic question and see the numbers, the context, and the sources together.

Finance

One definition per metric.

Approved metrics and shared definitions, so every answer traces back to the source and matches the board pack.

IT and security

Enable AI. Keep control.

Opt in source by source, inherit existing permissions, and keep an audit log of every query and agent action.

Before the first call

How Strata fits your company

What is Strata?

Strata is Cuesta’s AI foundation and the team that deploys it. It connects your structured and unstructured data, business definitions, and decision history into one governed layer, then makes that context available to employees and agents.

Do we need to replace our ERP or CRM?

No. Packaged applications stay as your systems of record. Strata connects to them, along with your warehouse and document repositories, and adds the knowledge layer AI needs on top.

Which AI tools can use it?

Company context is available in AI chat (Claude, ChatGPT, or an interface in your own app), in enterprise search, and to agents through APIs and MCP.

Who can see what?

Each source is added by explicit opt-in, and permissions are inherited from that source. Every answer carries lineage and citations, and every query and agent action is logged.

How is this different from rolling out chat licenses?

Licenses and training get most companies to the chat plateau: generic answers and work still finished by hand. Strata adds the context layer, shared skills, and agents that move value past that point.

How do we get started?

Start with one high-value workflow. We scope the sources and definitions it needs, deploy the foundation under it, and ship it in [timeline]. Book a conversation to begin.

More from Cuesta Partners

Strata is part of how we deliver data and AI.

Visit cuestapartners.com →

Insights

Cuesta and Keboola form a strategic partnership →

Read the Strata announcement.

What we do

AI Strategy and Execution →

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