# STRATIS

> STRATIS is a decision intelligence platform for enterprise marketing teams, made by Stratis Technologies Inc. in Toronto. It connects a brand's marketing channels and data, reasons across them continuously and brings the team ranked insights, each with its evidence, for a person to accept, question or reject.

This file summarizes stratis.technology for language models and agents. Every statement below comes from the site itself. The full text of every page is in [llms-full.txt](https://stratis.technology/llms-full.txt).

## What STRATIS does

- Connects channels and data in place: Meta, Google, TikTok, DV360, The Trade Desk, YouTube and retail media networks, plus file and warehouse feeds, normalized into one schema, refreshed daily and reconciled to the client's existing reporting before go-live.
- Reasons across the whole operation (brand, regions, product lines, audiences, campaigns and channels) instead of one channel at a time.
- Watches for anomalies, pacing and burn rate, segment patterns, creative fatigue and channel saturation. An insight fires only after a pattern has held for about three days.
- Ranks each insight by value to the business and attaches the signal, the recommended action, a plain-language rationale, the expected effect with its uncertainty and an audit trail.
- Routes insights through the client's approval workflow. A person accepts, questions or rejects every insight.
- Keeps every decision, its reasoning and what followed. This accumulated, client-owned context is called Reserve, and STRATIS reasons from it.

## Who it is for

- Enterprise marketing teams with many channels, regions, business lines or agencies, and the analytics, security and legal leads who review their decisions.
- Teams in financial services, automotive, retail, consumer goods and healthcare, including regulated environments.
- Independent agencies and networks that want to run client programs on STRATIS, with certified operators and the intelligence held by the client.

## Why teams choose it

- Decisions arrive while there is still time to act, instead of weeks later in a report.
- Every insight shows its evidence and reasoning, so the people who must defend a decision can.
- It sits on the client's side of the table: no media inventory, no required agency, no channel economics.
- A general-purpose model cannot see a brand's campaign data, brief, strategy, market and decision history at once; STRATIS reads all of them and shows the path it took.
- The intelligence belongs to the client and survives agency changes, team turnover and platform changes.

## Governance and security, as stated on the site

- Read-only: STRATIS reads from the client's systems and writes nothing back. It does not act on its own.
- Each client runs in an isolated environment. Data, memory and learnings never leave it, and no client's data trains any model.
- An append-only audit trail records every insight, model call and operator action with provenance, model version and data lineage.
- SSO, SAML and MFA, role-based access by region and line of business, and segregation of duties.
- Data is held in North America, with a named sub-processor register.
- SOC 2 Type 1: attested. An independent auditor has examined the design of STRATIS's security controls. A Type 2 report is not yet issued.

## How to engage

- Book a 30-minute working session: [stratis.technology/demo](https://stratis.technology/demo), or the calendar directly at [app.apollo.io/#/meet/brad_barclay_ffe/stratis](https://app.apollo.io/#/meet/brad_barclay_ffe/stratis).
- Email: hello@stratis.technology, also for security reviews and documentation.
- Pricing is not published. Engagements start with a working session on one live decision.

## Pages

- [Product](https://stratis.technology/product): how STRATIS connects, reasons, detects, shows evidence and learns
- [Insight engine](https://stratis.technology/insights): how an insight is built, detected, ranked and approved
- [Reserve](https://stratis.technology/intelligence): the client-owned decision memory
- [Enterprise](https://stratis.technology/enterprise): use cases, deployment pattern and governance
- [Trust](https://stratis.technology/trust): governance, data handling, calibration and controls
- [Agencies](https://stratis.technology/agencies): the agency partnership model
- [FAQ](https://stratis.technology/faq): direct answers to common buyer and security questions
- [See STRATIS in action](https://stratis.technology/demo): request a live demo or book a working session

## Optional

- [Company](https://stratis.technology/company): history, leadership, research foundation and principles
- [Careers](https://stratis.technology/careers): open engineering roles in Toronto
- [Full site text](https://stratis.technology/llms-full.txt): every page as Markdown
- [Privacy policy](https://app.stratis.technology/privacy)
- [Terms](https://app.stratis.technology/terms)