Claix is the controlled data retrieval layer for AI agents: it connects to your relational database and lets each agent retrieve only the tables and columns you allow, guided by your own rules and returned as validated results or typed answers, without moving your data. Available via REST API, MCP, and A2A.

How do I get started?

In three steps: connect your Postgres database with a read-only role (Claix drafts a Data Map for you to review), define routes and agents with your rules (no YAML or code), then call one endpoint so your agent gets live typed answers inside the perimeter you set.

Does Claix copy my data into a vector store?

No. Claix does not copy your data or build a vector index over it. Agents query your database where it lives, within the tables and columns you allow. Every query is validated before it runs and traced afterward.

Does Claix write to my database?

No. Claix connects with a read-only role. Loading documents into structured fields is a separate product, Claix Ingest, which you choose to use.

Which databases does Claix support?

Postgres today (including Postgres-compatible setups such as Supabase). You connect with a read-only role so agents never get write access through Claix.

What are routes and agents?

A route is a retrieval capability: the tables and columns allowed plus a short guide with your rules and vocabulary. An agent is the identity that uses them—its own endpoint, business prompt, attached routes, and response mode (raw results or reasoned typed answers). Create a route once and attach it to as many agents as you need.

How do I call a Retrieve agent?

POST to /retrieve/{agent_name} with a JSON body of questions (each with an optional format such as string, int, boolean, json, or array:string). You get typed answers in order plus a log_id. The same agent is also reachable over MCP (claix.retrieve.ask) and A2A.

What answer formats can I request?

In reasoned mode you can ask for string, int, boolean, timestamp, timestamptz, date, json, array:string, or array:int. Typed values mean your workflow can branch on booleans, use numbers and lists directly, and skip parsing free text.

How does pricing work?

With Claix Managed AI the fee is €0.10 per question. With your own LLM key (BYOK) from OpenAI, Google, Anthropic, or xAI, the Claix fee drops to €0.02 per question and you pay your provider’s tokens directly. Results with your own key depend on the model you choose—test in the Sandbox before going live.

Is agentic RAG the same as vector RAG?

No. They sit on different axes. “Agentic” is about who triggers retrieval (a fixed pipeline vs an agent calling a tool). “Vector” is about how results are matched (embeddings). An agent can call SQL, BM25, or embeddings; a fixed pipeline can use hybrid search. For relational business data, embeddings are often the wrong default.

Is SQL retrieval RAG?

Yes. RAG means retrieved information feeds the model. It does not require embeddings, and the retrieved information does not have to be text chunks. A SQL query that returns live records for the model is still retrieval.

When should I still use a vector database?

When you need semantic discovery over a large permanent text collection, heavy repeated search traffic, or a product where search is the product. For exact values, counts, dates, and live rows already in Postgres, query the database where it lives with scoped access instead of copying it into an index.

Can I use Claix from LangChain, Cursor, or n8n?

Yes. Claix is not an agent framework—it is a retrieval layer you call from the stack you already use. Call REST from any HTTP client (including n8n), expose the agent as an MCP tool for Cursor and compatible clients, or connect over A2A so other agents can delegate data questions.

What happens when the answer is not in the allowed tables?

The field comes back empty instead of a guess. Queries only run inside the routes you attached to the agent; everything outside that perimeter does not exist for them. Traces show what was asked, which route answered, and what came back.

How is Claix different from giving an agent a database MCP server?

A generic database MCP connection is quick to wire up, but the access model depends on the server and the role you attach. Claix adds routes, per-agent allowlists, validation before queries run, typed multi-question answers, and a reviewable trace—so you define the boundary once and enforce it on every call.

An enterprise semantic layer for AI agents. According to its site, it builds a semantic graph of your data automatically and compiles agent requests into governed SQL.

How much does Colrows cost?

Colrows doesn't publish its prices. Its pricing page describes one committed annual figure priced on natural-language requests, with tier figures disclosed on request. Its AWS Marketplace listing shows a Consumption Token at $0.30.

Does Colrows have a free trial?

Its pricing page lists a free Shared SaaS proof of concept for qualified prospects, with one data source for 30 to 60 days.

Can I bring my own LLM with Colrows?

According to its pricing page, only on on-premise and private VPC deployments. On Shared SaaS the model is managed by Colrows.

Which databases does Colrows support?

Colrows says it supports more than 16 SQL engines, including Postgres, Snowflake, Databricks, BigQuery and Redshift.

What are the best alternatives to Colrows?

It depends on what you need. Cube fits governed metrics and BI. Wren AI fits open-source semantic modeling. A framework fits teams who want to build in code. A managed layer such as Claix fits agents in production on Postgres or Supabase with pay-per-question pricing.

How does Colrows compare with Cube?

Both are semantic layers. Colrows builds its model automatically and is sold on a committed annual figure, while Cube has you model your data in code and publishes seat-based prices. Both describe themselves as ready for AI agents, so test each on your own data.

How does Claix pricing compare with Colrows?

A direct comparison isn't possible because Colrows doesn't publish its figures. Claix charges per question with no commitment. Ask Colrows for a quote based on your expected volume and compare it with your expected number of questions on Claix.

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Comparison · AgentsOctober 24, 2026ByGael Anaya

Colrows alternatives (2026): pricing, approach and options

Looking for a Colrows alternative? How Colrows prices and works, who it fits, and options if you need self-serve, per-question pricing or Postgres-first.

Claix · Updated October 2026 · Colrows details as published by Colrows (its pricing page is dated August 2026). Disclosure: we build Claix, which is one of the alternatives below. We kept the Colrows sections to what Colrows itself publishes, and we say where we couldn't find information. Related: Cube alternatives (/blog/cube-alternatives), safe Postgres access (/blog/how-to-let-an-ai-agent-query-postgres-safely), Vanna alternatives (/blog/alternatives-to-vanna-text-to-sql), database access layers (/blog/best-database-access-layer-for-ai-agents). Product: https://www.claix.dev/. Pricing: https://www.claix.dev/#precios. Re-check Colrows' pricing page before every update.

Quick answer

Colrows is a semantic layer for enterprise AI agents. It builds a model of your data automatically and compiles each agent request into governed SQL. It is sold on a committed annual figure priced on natural-language requests, and the figures are disclosed on request. Teams look for alternatives when they want to start without a sales process or an annual contract, pay as they go, work mostly with Postgres or Supabase, or choose their own LLM on a hosted plan (Colrows allows that only on on-premise and private VPC deployments). The main alternatives are Cube (a semantic layer you model yourself, priced per developer seat plus compute), Wren AI (an open-source semantic layer), a framework such as LangChain, a database MCP server for development, and a managed layer such as Claix (self-serve, pay per question, Postgres and Supabase).

What is Colrows?

Colrows describes itself as an autonomous semantic layer for enterprise AI, and as a semantic execution layer. In its words, it builds a semantic graph of your data automatically and compiles each agent request into governed, deterministic SQL for the database in use, with joins checked in advance and role-based and attribute-based access enforced.

It doesn't copy your data. Colrows' AWS Marketplace listing says it sits above your warehouse, compiles the semantics and passes governed SQL down, and that your data stays in your environment.
The semantic model is built automatically. The same listing says Colrows crawls your databases, Confluence, BI reports and user feedback to build and maintain the model, and detects schema drift automatically.
Colrows says it supports more than 16 SQL engines, including Postgres, Snowflake, Databricks, BigQuery and Redshift, and more than 8 LLMs. Besides an API for agents (the Semantic Resolution API), it includes a chat interface for analysts (the AI Analyst) and question answering over connected documents.

How is Colrows priced?

Item	What Colrows publishes
Pricing unit	Natural-language requests: a question in the AI Analyst, or a request through the Semantic Resolution API. One agent call counts once, however many internal steps it takes.
Contract	One committed annual figure, paid annually in advance, on terms of 12, 24 or 36 months, invoiced in USD.
Shared SaaS tiers	Essential, Professional, Business and Enterprise, with request capacity sized per tier. The annual figures are disclosed on request.
Users	Unlimited. No per-seat charge.
Not metered	Dashboards, reports, embedded views, retries and internal model calls.
Going over capacity	A notice at 80 percent, a soft band up to 110 percent, then new questions pause until the next cycle or until you approve an optional query pack. No overage invoice.
Maintenance (SaaS)	Charged per governed semantic asset, fixed at contract.
Onboarding	A one-time setup engagement.
On-premise or private VPC	Licence tiers (Team, Standard, Enterprise, Group), with the annual figure on request. You run the model, and bringing your own LLM is allowed here.
Trial	A free Shared SaaS proof of concept for qualified prospects: one data source, 30 to 60 days.
Renewals	On multi-year terms, the full schedule is fixed at signing, with each year capped at a 3 percent increase.
Embedded or OEM	Priced per engagement.
Forward-deployed engineering	An optional engagement where a Colrows engineer deploys in your cloud and hands over in eight weeks. The pilot fee is credited toward a subscription if you convert within 90 days.

Colrows' AWS Marketplace listing shows a single usage dimension called the Colrows Consumption Token, priced at $0.30. The listing doesn't say how many questions one token covers, so we can't translate it into a per-question price. The model is predictable by design: a fixed annual figure and no surprise bills. It is also an enterprise-style, sales-led model.

What Colrows doesn't publish

The annual figure for each tier, and how many requests each includes.
The price per governed semantic asset for maintenance.
What a Consumption Token equals in questions.

Without those numbers, nobody outside a sales conversation can calculate what Colrows would cost for a given volume. If you evaluate it, ask for a quote based on your expected number of questions.

Why teams look for Colrows alternatives

Sales-led buying. The pricing page points to booking a demo or a proof of concept for qualified prospects, and figures are disclosed on request.
An annual commitment. You sign a committed figure for 12 to 36 months. If you want to pay only for what you use, from the first question, it is a different model.
No choice of model on SaaS. The pricing page says that on Shared SaaS the model is managed by Colrows and can't be substituted. Bringing your own LLM is possible only on on-premise and private VPC deployments.
Built for large data estates. Sixteen or more engines, SSO, a 99.99 percent uptime target and forward-deployed engineers are valuable at enterprise scale. A small team with one Postgres database may not need them.
A maintenance fee on SaaS for keeping the semantic graph current, on top of the subscription.

Colrows alternatives at a glance

Option	Approach	Published pricing model	Deployment	Best for
Colrows	Automatic semantic graph, compiled governed SQL	Committed annual figure, per question; figures on request	SaaS, private VPC, on-premise, air-gapped	Enterprises with many data sources
Cube	A semantic layer you model; SQL, REST, GraphQL and MCP	Per developer seat ($40 or $80 a month) plus compute; Enterprise custom	Cube Cloud, or the open-source core self-hosted	Governed metrics for BI, embedded analytics and AI
Wren AI	Open-source semantic layer	Open source	Self-hosted	Analytics teams that will do the modeling
LangChain or similar	You build the agent	Open source; you pay for infrastructure and the model	Your own code	Teams with engineering time
Database MCP servers	A tool that connects an AI client to a database	Usually free	Your machine or your cloud	Development and testing
Claix	You choose tables and columns per agent; a model writes the SQL within that scope	Pay per question; see the Claix pricing page	Hosted service	Agents in production on Postgres or Supabase

The options in more detail

Cube

Cube is the best-known open-source semantic layer. Its core is open source under the Apache 2.0 license and can be self-hosted, and Cube Cloud is the managed product. You model metrics, dimensions, joins and access rules in code, and agents query that model over MCP, SQL, REST or GraphQL. See our Cube alternatives article (/blog/cube-alternatives) for its pricing and approach in detail.

Wren AI

Wren AI is an open-source project built around a semantic layer: you define business terms first, and SQL is generated from those definitions. A September 2026 comparison by Querio, a vendor in the same space, described it as actively maintained, supporting Postgres among other databases, and requiring semantic modeling up front.

Frameworks such as LangChain

Frameworks give you the building blocks. LangChain's own documentation says running model-generated SQL carries inherent risks, advises scoping database permissions as narrowly as possible, and describes its tutorial tools as minimal demonstration wrappers that need your own validation. You own the safeguards.

Database MCP servers

Useful while you build. Supabase's documentation says its MCP server is designed for development and testing, and offers a read-only mode and project scoping.

Claix

Claix is a hosted service between your agent and your database. You connect Postgres or Supabase with a read-only role, choose the tables and columns each agent can use, and write a short guide with your business rules. Each agent gets an endpoint over REST, MCP or A2A, and returns validated results or typed answers. Every request is traced. You pay per question, with no seats and no annual commitment. Current rates are on the pricing page (managed AI at 0.10 euros per question, or 0.02 euros per question with your own LLM key, plus your provider's token costs).

Colrows vs Claix, side by side

	Colrows	Claix
How the SQL is produced	Compiled from an automatically built semantic graph; Colrows describes it as deterministic	Written by a model within the tables and columns you allow, and validated before it runs; not deterministic
Setup	Metadata crawl and semantic graph construction as a setup engagement; optional forward-deployed engineer	Connect a read-only role, choose tables and columns, write a guide
Data sources	16+ engines, including Postgres and major warehouses	Postgres and Supabase today
Pricing unit	Natural-language requests, in a committed annual figure	Questions, pay as you go
Commitment	12 to 36 months	None
Trial	Free proof of concept for qualified prospects	Free questions to start
Model choice	Managed by Colrows on SaaS; your own LLM only on-premise or in a private VPC	Claix Managed AI or your own key
Deployment	SaaS, private VPC, on-premise, air-gapped	Hosted service
Access control	Role-based and attribute-based access, enforced at compile time	Access scoped per agent through its routes; per-end-user rules stay in your database or app
Typical buyer	Enterprise data and AI teams	Developers and small teams shipping agents

When Colrows is the better choice

You have many data sources and warehouses, not just one database.
You need on-premise, private VPC or air-gapped deployment.
You want a semantic model built and maintained automatically, and deterministic compiled SQL.
You need role-based and attribute-based access enforced per user.
You prefer a fixed annual budget and a vendor that deploys with you.

When an alternative may fit better

You want to start today and pay only for the questions you ask.
Your data is in Postgres or Supabase and your agents answer operational questions.
You want to choose your own LLM on a hosted plan.
You have no procurement process and want to test with real data in an afternoon.
You want to keep the agent logic in your own code and only need controlled access.

Questions to ask any vendor before you sign

What exactly counts as one billable unit?
What happens when I exceed my capacity, and what does extra capacity cost?
What is the minimum term and the minimum spend?
Who builds and maintains the semantic model, and what does that cost?
Can I choose or bring my own LLM, and on which plans?
Where does my data flow, and what is stored?
How do I export my configuration if I leave?

Sources

Claims about Colrows come from Colrows' own pricing page (dated August 2026 in their materials) and AWS Marketplace listing, checked around October 2026. Claims about Cube, Wren AI, LangChain and Supabase MCP come from their documentation or independent comparisons cited elsewhere on this blog. Re-check before you commit.

Frequently asked questions

What is Colrows?: An enterprise semantic layer for AI agents. According to its site, it builds a semantic graph of your data automatically and compiles agent requests into governed SQL.
How much does Colrows cost?: Colrows doesn't publish its prices. Its pricing page describes one committed annual figure priced on natural-language requests, with tier figures disclosed on request. Its AWS Marketplace listing shows a Consumption Token at $0.30.
Does Colrows have a free trial?: Its pricing page lists a free Shared SaaS proof of concept for qualified prospects, with one data source for 30 to 60 days.
Can I bring my own LLM with Colrows?: According to its pricing page, only on on-premise and private VPC deployments. On Shared SaaS the model is managed by Colrows.
Which databases does Colrows support?: Colrows says it supports more than 16 SQL engines, including Postgres, Snowflake, Databricks, BigQuery and Redshift.
What are the best alternatives to Colrows?: It depends on what you need. Cube fits governed metrics and BI. Wren AI fits open-source semantic modeling. A framework fits teams who want to build in code. A managed layer such as Claix fits agents in production on Postgres or Supabase with pay-per-question pricing.
How does Colrows compare with Cube?: Both are semantic layers. Colrows builds its model automatically and is sold on a committed annual figure, while Cube has you model your data in code and publishes seat-based prices. Both describe themselves as ready for AI agents, so test each on your own data.
How does Claix pricing compare with Colrows?: A direct comparison isn't possible because Colrows doesn't publish its figures. Claix charges per question with no commitment. Ask Colrows for a quote based on your expected volume and compare it with your expected number of questions on Claix.

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