Governed answers for people and the agents they trust
Nexatron connects to the warehouses you already run and generates the semantic layer your AI needs. People and AI agents get the same calibrated, governed answers, in plain English, by voice, or over MCP.
Our partner ecosystem
AI needs the meaning behind your data.
The definitions and join logic that make a number trustworthy live in people's heads and old SQL, not in your warehouse. Without them, AI answers on raw tables and gets confidently wrong.
Nexatron generates your semantic layer.
It reads your existing schemas and queries to build the metric definitions, joins, and rules your AI needs. As the business changes, Nexatron proposes updates and routes them to a person for review, so every change stays versioned and governed.
One question, answered across every source you run.
Enterprise data never lives in one platform. Nexatron joins across your warehouses and business apps with lineage preserved, no warehouse migration required.
Snowflake
Google BigQuery
Databricks
Amazon Redshift
Salesforce
NetSuite
HubSpot
ServiceNow
Amazon S3 / Parquet
DuckDB
Microsoft Excel
Google SheetsThree ways to ask. One engine checks every answer.
Conversational BI
Trusted, explainable insights with deep analysis, built-in governance, and lineage on every claim.
AI-powered dashboards
Dashboards built on certified metrics. When a number changes, the lineage shows why.
Analytics agents
Agents that query your data under the asker's permissions, with every call logged and auditable.
A fixed suite of golden questions runs against every release.
Welcome back, Sam
One semantic layer. Everyone gets the same answer.
People asking in chat. Agents calling over MCP. Dashboards subscribing to a metric. All of them hit the same governed semantic layer and get the same number.
Switch between Analyst and Agent: the question and the answer match, down to the same confidence score.
Enterprise expansion ARR accelerated +22%. New pricing lifted mid-market ACV by $14K. The partner channel closed its first two enterprise accounts in week 11.
Your product. Our answer engine.
Drop governed conversational analytics into your own app. Your customers ask under your brand and get answers that respect your security model, with lineage attached.
Any MCP agent becomes a governed analyst.
Connect Claude, Copilot, or your own agents to the Nexatron MCP server. They inherit the same governed context and calibrated confidence your people get. Agent queries run under row-level security and land in the same audit log as human queries. With bring-your-own LLM keys, model calls run on your provider contract.
EMEA and LATAM. EMEA closed at 112% of plan on enterprise expansion; LATAM hit 106% in the first full quarter of the partner program.
Before Nexatron, our exec team waited eleven days for a revenue question to come back from analytics. Now they ask it in Slack and get the answer, with its sources, in under a minute.
Agents follow the same guidelines as people.
Every query runs under row-level security and masking, whether a person or an agent sent it. All of it lands in the audit log.
Flexible deployment
Governance
Security
Frequently asked questions
What Nexatron is, how it stays accurate, and how it keeps your data governed — for the people and the agents asking the questions.
What is Nexatron?
Nexatron is an enterprise AI analytics platform by dotSolved. You connect your data warehouse, then anyone — a person in chat or an AI agent over MCP — can ask questions in plain language and get answers governed by your security rules. Every answer comes back with the exact query that produced it, its data lineage, and a confidence score.
What is a semantic layer?
A semantic layer is the shared definition of what your data means: which metrics are certified, how tables join, and which business rules apply. Nexatron's semantic layer, MetricQL, captures those definitions once so that every question is answered against trusted, governed logic instead of raw tables. It is what lets AI answer correctly instead of guessing at column names.
How does governed natural-language-to-SQL work, and how is it kept accurate?
Nexatron translates a question into SQL against your certified metrics and semantic layer, not against raw tables. The model's output is treated as untrusted and validated against the schema and your governance rules before any query is allowed to run. Each answer returns the rows, the exact generated SQL, its lineage, and a confidence score, so accuracy is verifiable rather than assumed.
Which AI assistants can connect over MCP?
Any MCP-capable assistant — including Claude, ChatGPT, and Cursor — can connect to Nexatron's hosted MCP endpoint. The connection uses Streamable HTTP with JSON-RPC 2.0 and OAuth 2.1 with PKCE and Dynamic Client Registration. Agents can run governed asks, discover and execute certified metrics, take actions with dry-run or execute, and run multi-step workflows — all under the same governance and audit trail as a human user.
Which data sources can I connect?
Nexatron ships nine warehouse and database connectors: Snowflake, Google BigQuery, Amazon Redshift, Databricks, PostgreSQL, MySQL, Microsoft SQL Server, Amazon S3/Parquet, and DuckDB. DuckDB also serves as the embedded engine that federates queries across these sources. Beyond the warehouses, a separate and growing library of business-app connectors — including Salesforce, QuickBooks, NetSuite, ServiceNow, HubSpot, Stripe, Microsoft Dynamics 365, and Atlassian — connects SaaS applications with per-user OAuth, so reads run under each user's own permissions. The full live catalog is at nexatron.io/connectors.
How is my data isolated and secured in a multi-tenant platform?
Every query filters by tenant, and four-layer row-level security is enforced on every request whether it comes from a person or an agent. Your warehouse credentials are stored as AES-256-GCM encrypted values in the connections table, managed through the Connections UI. Your data and queries are never used to train foundation models, and Nexatron is SOC 2 Type I attained (Type II in progress), ISO 27001 certified, and GDPR-aligned.
What is a calibrated answer?
A calibrated answer is one that ships with everything you need to trust it: the result rows, the exact query Nexatron generated, the data lineage behind it, and a confidence score. Instead of an unexplained number, you get a number you can audit and defend. Low-confidence answers are flagged so people and agents know when to verify before acting.
Do people and AI agents get the same answers?
Yes. Whether a question arrives from a person in chat or from an AI agent over MCP, it runs through the same semantic layer, the same certified metrics, and the same four-layer row-level security. Every query — human or agent — lands in the same audit log. There is no separate, less-governed path for machines.