Token burn
Raw API payloads get stuffed into the context window, call after call. Costs scale with every question and every user.
Sageivo sends only the relevant schema and gets back computed results.
Agentic Data Intelligence Platform
Ask your business anything. Get answers you can verify.
Bring all your business data together in one place. Ask questions, build AI agents, create dashboards and uncover insights through simple conversations. Connect your existing data warehouse or let us build one for you.
- Your cloud. Your data. Your choice of LLM.Runs in your AWS, Google Cloud, Azure or on-prem.
- The software is free.You only pay for the expertise to deploy, manage and evolve it.
Which campaigns drove the most closed-won revenue last quarter?
metadatasqlvalidaterun as youverify
Integrations
Every tool your business runs on. One place to ask.
CRM, sales calls, ads, support, docs, chat, email and finance. Connect your existing warehouse, or we build one and pipe in anything with an API or a database.
Supported sources include Salesforce, HubSpot, Gong, Google Ads, Meta Ads, LinkedIn Ads, Zendesk, Intercom, Jira, Confluence, Slack, Gmail, Outlook, Google Analytics 4, Stripe, NetSuite, QuickBooks, Xero, Shopify, Marketo, Pipedrive, Freshdesk, ServiceNow, Notion, Asana, Workday, PostgreSQL, MySQL and custom APIs.
Warehouses
LLMs
Clouds
$0Software license. Forever.
0Per-seat or per-query fees
1Governed source of truth for every tool
100%Your cloud, your keys, your data
The problem with MCP-based "chat with your tools"
MCP servers were built for actions, not for data intelligence.
Wiring an LLM to a dozen SaaS APIs looks easy in a demo. Ask a real cross-tool question and it falls apart: thousands of tokens per call, API row limits, rate limits, no joins, no shared definitions, and a license for every person in every tool.
LLM + 8 MCP servers
fan-outTokens0
Time0s
Accuracy60% low
Sageivo + governed warehouse
one queryTokens0
Time0s
Accuracy100% high
Illustrative run of one cross-tool question: "Which accounts with open P1 tickets also had pricing objections on Gong calls?"
Slow
Sequential API calls, pagination and retries mean answers take a minute or more, and often time out.
One warehouse query, typically seconds.
Inaccurate
The model guesses how a HubSpot contact maps to a Zendesk user. Duplicates get double-counted. Nobody can audit the math.
Resolved entities, verified joins, visible SQL.
No context
APIs don't know that "revenue" means recognized revenue excluding voided invoices. Every user's answer is different.
Shared metrics, glossary and guidance in Knowledge Studio.
Limited data
Row caps, page limits and short retention windows. You can't trend three years of pipeline through a 100-records-per-call API.
Full history, every row, in your warehouse.
License sprawl
To ask about Gong, Salesforce and Zendesk via MCP, every employee needs a seat in Gong, Salesforce and Zendesk.
Access is governed in the warehouse, not by SaaS seats.
How it works
All your data in one place, understood, then made conversational.
We do the hard part that every "AI for data" tool skips: getting clean, related, governed data into one warehouse you own.
-
01
Connect every source
We build and run the ETL jobs for every tool with an API, on a schedule you choose.
- CRM, sales calls, ads, support
- Docs, tickets, chat, email
- Finance, billing, product DBs
-
02
Unify and deduplicate
Entity resolution merges the same customer, company or person across every tool into one record.
- Golden records
- Consistent IDs and types
- Full change history
-
03
Model relationships and meaning
We map how datasets join and capture your business definitions so the AI uses them every time.
- Verified joins, keys, grain
- Approved metrics and glossary
- Plain-English guidance
-
04
Ask, chart, share, automate
Your team chats with the data, saves live dashboards, and builds agents, all on the same governed layer.
- Answers with SQL and sources
- Dashboards for every team
- Agents and scheduled reports
salesforceAcme Corporation · acct 0013x…
hubspotACME Corp. · acme.com
zendeskacme · ops@acme.com
stripeAcme Corp · cus_Nf4…
customer_id 48213 · Acme Corporation
4 sourcesARR $186k3 open tickets12 Gong calls
entity resolution4 → 1
Why our answers are trustworthy
The AI is only as accurate as the data underneath it. So we fix the data first.
- Deterministic SQL, not guesses. Every number comes from a real query against your warehouse.
- Validated before it runs. SQL is checked for structure, referenced objects and cost, then executed read-only.
- Verified after it runs. A verifier compares the question, SQL and result shape, and repairs or asks when something doesn't fit.
- Fully auditable. See the SQL, the sources, the assumptions and how fresh the data is, on every answer.
The Sageivo platform
Everything your team needs to work with data, without a data team on every question.
Ask Data: chat with your warehouse
Plain-English questions, streaming answers, follow-ups that remember context. Every answer comes with an interactive table or chart, the SQL behind it, the sources used and data freshness.
-- "Pipeline created by channel, last 6 months" SELECT channel, DATE_TRUNC(created_at, MONTH) m, SUM(amount) FROM crm.opportunities JOIN marketing.touchpoints USING(contact_id) WHERE created_at >= DATE_SUB(CURRENT_DATE(), INTERVAL 6 MONTH) GROUP BY 1, 2
Bring your own LLM
Use the models you already trust and pay for. Admins decide which ones are allowed.
Charts and live dashboards
Pin any answer as a chart or KPI. Dashboards refresh under each viewer's own permissions.
ARR$4.2M
Win rate27%
CSAT94
Agents and automations
Build shareable agents that monitor metrics, answer recurring questions and send scheduled reports, with the same governance as chat.
Share with your team
Share dashboards and conversations, not data privileges. Everyone only ever sees what their warehouse identity allows.
Data Knowledge Studio
Teach the AI your business: table and column descriptions, approved metrics, glossary synonyms, verified joins and plain-English rules like "use invoice_date for revenue, exclude voided invoices". Versioned, reviewable, and never overwrites source metadata.
Permission-aware by design
Every query runs as the person asking, using their own warehouse identity. Project, dataset, table, column and row policies are enforced by the warehouse itself. Even app admins don't get extra data access.
Exports, feedback and continuous improvement
Download tables, charts and reports, including very large exports. Users flag answers with a thumbs-down or "send to admin", and your admins (or our team) turn that feedback into better metadata, so accuracy compounds over time.
Security and control
Runs in your cloud. Your data never leaves it.
Sageivo is self-hosted inside your AWS, Google Cloud or Azure account, or on your own hardware. You hold the keys, the network boundary and the audit trail. We manage it for you, with the access you grant.
- No data copied to us. Business data stays in your warehouse; we don't run a shared multi-tenant cloud.
- User-delegated queries. Each question runs with the asker's own warehouse permissions.
- Read-only, bounded SQL. Validated, cost-estimated and limited before execution.
- Secrets in your secret manager. Encrypted credentials, private networking, your own LLM endpoints.
your-cloud-account · private VPC
SalesforceHubSpotGongZendeskAds+ more
ETL jobsscheduled
WarehouseBigQuery · Snowflake…
Your LLMBedrock · Vertex · Azure
SSOyour IdP
Sageivoapp + app DB
Audit logsyour SIEM
The economics
A modern data stack, without the modern data stack bill.
The usual route is an ETL subscription, a BI tool priced per seat, an AI add-on, consultants, and licenses in every SaaS tool so people can query it. That easily runs to tens of thousands of dollars a month. We replace it with a one-time build, often funded by your cloud provider, and a predictable service plan.
Typical stack
$10k–$50k+ /mo
- Managed ETL / ELT (usage-based)$$$$
- BI tool, per seat$$$
- AI add-on, per seat$$$
- Extra SaaS seats for MCP access$$$
- Consultants for every change$$$$
Sageivo
$0 software
- Warehouse + ETL buildoften cloud-funded
- Sageivo license$0
- Per-seat / per-query fees$0
- Cloud + LLM usagebilled by your provider
- Managed service planquoted for your scope
Typical-stack range reflects common list pricing for mid-sized teams; your numbers will vary. Cloud and LLM usage are paid directly to your provider.
Path 01
Cloud-funded build
We help you apply for AWS, Google Cloud or Azure partner funding and credits. When approved, your warehouse build costs you nothing.
Path 02
Starter sources, on us
No funding? We build a starter set of data sources at no cost in exchange for a longer-term service commitment.
Path 03
Bring your warehouse
Already have BigQuery, Snowflake or Redshift? We connect Sageivo, model the metadata and you're live fast.
What we believe
Software should be free
Software should be free. The people who make it work for you are what's worth paying for.
Sageivo has no license key, no seat counter and no usage meter. Our service plan pays for engineers who build your pipelines, keep everything patched and running, and ship the features your business needs. If we stop being useful, you keep the software and the warehouse.
$0Software license
∞Users and seats
∞Questions and dashboards
YouOwn the warehouse
Who we are
Data and cloud engineers who've built this at enterprise scale.
We're a team of professionals with deep experience in data engineering, AWS and Google Cloud, building enterprise-grade warehouses, pipelines and data platforms. Sageivo is the platform we wished our clients had.
Data engineeringWarehouses, ETL/ELT, modelling, entity resolution and data quality.
AWSRedshift, Bedrock, ECS, RDS, IAM and secure networking.
Google CloudBigQuery, Vertex AI, Cloud Run, Cloud SQL and governance.
Applied AIText-to-SQL, verification, agents and LLM cost control.
FAQ
Questions, answered.
What is Sageivo?
Sageivo.ai is a self-hosted Agentic Data Intelligence Platform. We build a governed data warehouse from all of your business tools and install Sageivo on top so anyone in your company can ask questions in plain English and get verified, SQL-backed answers, charts, dashboards and agents. It runs in your own AWS, Google Cloud, Azure or on-prem environment.
Is Sageivo really free?
Yes. There's no software license, no per-seat fee and no per-query fee. You pay for a service plan that covers deployment, maintenance, data pipelines, support and the custom features you need. It's quoted for your number of data sources and support level. Cloud and LLM usage are billed by your own providers.
Why is a data warehouse better than MCP servers for AI agents and data intelligence?
MCP servers make the model call each SaaS API live. For data intelligence that burns tokens, is slow, hits API row and rate limits, can't reliably join data across tools, has no shared business definitions, and usually requires every employee to hold a license in every tool. A governed warehouse already has the data joined, deduplicated and described, so the AI writes one SQL query and returns an answer you can verify. Read the full comparison.
Which data sources and warehouses do you support?
Any tool with an API, including Salesforce, HubSpot, Gong, Google Ads, Meta Ads, LinkedIn Ads, Zendesk, Jira, Confluence, Slack, Gmail and Outlook, Stripe, NetSuite, QuickBooks, Shopify and your own databases. The warehouse can be BigQuery, Snowflake, Amazon Redshift, Azure Synapse or Fabric, PostgreSQL, Databricks or on-premises.
Can we use our own LLM?
Yes. Sageivo works with OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock, Google Vertex AI and Azure OpenAI, using your own keys or your cloud's managed models. Admins choose which models are allowed.
How much does the data warehouse build cost?
Often nothing. We help you apply for cloud-provider funding programs and credits on AWS, Google Cloud and Azure. If funding isn't available, we can build a starter set of data sources at no cost in exchange for a longer-term service commitment.
Where does our data live?
In your own cloud account or data center. Sageivo is deployed inside your environment, queries run with each user's own warehouse permissions, and your data isn't copied to our servers. See our security overview.
How accurate are the answers?
Accuracy comes from the data layer, not from prompt tricks. Because the warehouse is deduplicated, related and documented, the AI writes deterministic SQL against known tables and approved metrics. Every query is validated before it runs and checked after, and you can always inspect the SQL and sources. When a question is ambiguous, Sageivo asks rather than guesses.
Start with a 30-minute call
Let's put all your data in one place and let your team talk to it.
Tell us which tools you run on and which cloud you use. We'll map the sources, check funding eligibility and show you Sageivo on a sample warehouse.