Chat with your data,
answers you can trust

Connect your database. Our agents make it AI-ready in hours — no hallucinations, no 6-month project.

Book a demo

See how it works

WHY IT MATTERS

Every team wants to chat with their data reliably. Plugging ChatGPT, Claude, or an MCP into your database doesn't work — hallucinations, inconsistent answers, no governance. No semantic understanding. No entity relationships. No business context. No memory. That's the gap.

APPLICATIONS

We built the layer between
your database and everything else.

Conversational analytics

AI agents & workflows

Ask. Answer. Move on.

Plain English in, reliable answers out.

Everyone self-serves: users, sales, CS, ops, execs.

Governance by design, every answer defensible.

White-label embedding that feels native in your product

SEE IT IN ACTION

Analytics chat

Query your data in plain English

How did sales perform last week?

Sales were up 15% last week with 320 new deals closed. Your results:

Ask anything about your data

Conversational analytics

Ask. Answer. Move on.

Plain English in, reliable answers out.

Everyone self-serves: users, sales, CS, ops, execs.

Governance by design, every answer defensible.

White-label embedding that feels native in your product

SEE IT IN ACTION

Analytics chat

Query your data in plain English

How did sales perform last week?

Sales were up 15% last week with 320 new deals closed. Your results:

Ask anything about your data

AI agents & workflows

The interface for machines.

One API for MCP, custom agents, workflows.

Structured, hallucination-free JSON agents can act on.

Powers recommendations, summaries, alerts, classifications.

Ship as React component, REST API, or SDK.

SEE IT IN ACTION

Agent capabilities

Plug your agents into your data.

Recommendations

Personalized outputs per user or account.

Smart digest

Turn raw data into daily briefings.

Proactive alerts

Trigger actions the moment signals appear.

Configure

Conversational analytics

Ask. Answer. Move on.

Plain English in, reliable answers out.

Everyone self-serves: users, sales, CS, ops, execs.

Governance by design, every answer defensible.

White-label embedding that feels native in your product

SEE IT IN ACTION

Analytics chat

Query your data in plain English

How did sales perform last week?

Sales were up 15% last week with 320 new deals closed. Your results:

Ask anything about your data

AI agents & workflows

The interface for machines.

One API for MCP, custom agents, workflows.

Structured, hallucination-free JSON agents can act on.

Powers recommendations, summaries, alerts, classifications.

Ship as React component, REST API, or SDK.

SEE IT IN ACTION

Agent capabilities

Plug your agents into your data.

Recommendations

Personalized outputs per user or account.

Smart digest

Turn raw data into daily briefings.

Proactive alerts

Trigger actions the moment signals appear.

Configure

BENEFITS

Built different.
Made for the new world.

The first data layer that's AI-ready and self-configuring.

Live in hours, not quarters

No prep work. No schema documentation. No six-week kickoff. Connect your database, get a working version the same day.

Auto-everything

Semantic mapping, business context, compounding learning — all automated, all improving with every query.

Answers you can trust

Accurate results from ambiguous questions. No hallucinations, no guesswork — just reliable answers to act on.

One layer, every consumer

End users, internal teams, product features, AI agents — all consuming the same intelligence layer.

Enterprise-ready from day one

BYOC deployment, multi-tenancy, authentication, data segregation. We built the hard stuff so you can ship the interesting stuff.

Context from the real world

We pull in external context — market data, news, your wikis — to bridge the gap between "what" and "so what".

Book a demo

10K+ DATA INSIGHTS DELIVERED

HOW IT WORKS

Developer experience

Book a demo

Feels simple.
Ridiculously powerful.

The magic happens before the question is even asked.

Step 1

Connect your data

Point us at your app database or warehouse. PostgreSQL, BigQuery, Snowflake — whatever you've got.

Step 2

We map your data automatically

Our agents crawl your schema, index values, infer relationships, and build the semantic layer that makes it actually work.

Step 3

We learn your business

Automated company research. Knowledge base ingestion. Domain terminology. The more you use it, the smarter it gets.

Step 4

Use it everywhere

Embed a chat for end users. Give teams a query console. Power features via API. Expose it to agents. Same layer, infinite applications.

HOW IT WORKS

Developer experience

Book a demo

Feels simple.
Ridiculously powerful.

The magic happens before the question is even asked.

Step 1

Connect your data

Point us at your app database or warehouse. PostgreSQL, BigQuery, Snowflake — whatever you've got.

Step 2

We map your data automatically

Our agents crawl your schema, index values, infer relationships, and build the semantic layer that makes it actually work.

Step 3

We learn your business

Automated company research. Knowledge base ingestion. Domain terminology. The more you use it, the smarter it gets.

Step 4

Use it everywhere

Embed a chat for end users. Give teams a query console. Power features via API. Expose it to agents. Same layer, infinite applications.

INTEGRATIONS & DEVELOPER EXPERIENCE

Setup so smooth,
it feels like cheating.

Tasks

Connect & setup

47 tables synced

1

2

3

4

5

6

7

8

9

10

# Terraform to setup resources and accesses


resource "aws_lambda_permission" "magemetrics_api_access" {

service = "internal-api"
location = "europe-west6"
role = "roles/run.invoker"
member = "serviceAccount:acme-corp@mm-prod.iam.gserviceacc.com"

}


~

Step 1

Connect your data

Direct connection to your app database or warehouse — PostgreSQL, BigQuery, Snowflake, whatever you're running.

For strict data policies, we propose BYOC: raw data never leaves your premises.

Tasks

Connect & setup

47 tables synced

1

2

3

4

5

6

7

8

9

10

# Terraform to setup resources and accesses


resource "aws_lambda_permission" "magemetrics_api_access" {

service = "internal-api"
location = "europe-west6"
role = "roles/run.invoker"
member = "serviceAccount:acme-corp@mm-prod.iam.gserviceacc.com"

}


~

Step 1

Connect your data

Direct connection to your app database or warehouse — PostgreSQL, BigQuery, Snowflake, whatever you're running.

For strict data policies, we propose BYOC: raw data never leaves your premises.

Tasks

Building semantic layer

60%

Indexing schema

25m 12s

Inferring relationships

9m 07s

Sampling statistics

12m 45s

Enriching business context

1m 23s

Finalizing semantic layer

Step 2

Auto-semantic layer

Our agents crawl your schema, infer relationships, and build a semantic layer that maps language to accurate queries.

Then we research your company — pulling in domain terminology, external context, and business logic.

No YAML files. No six-week onboarding. The layer updates automatically as your data evolves.

Tasks

Building semantic layer

60%

Indexing schema

25m 12s

Inferring relationships

9m 07s

Sampling statistics

12m 45s

Enriching business context

1m 23s

Finalizing semantic layer

Step 2

Auto-semantic layer

Our agents crawl your schema, infer relationships, and build a semantic layer that maps language to accurate queries.

Then we research your company — pulling in domain terminology, external context, and business logic.

No YAML files. No six-week onboarding. The layer updates automatically as your data evolves.

Tasks

Integration options

1

2

3

const mage = new MageClient({ apiKey: MM_KEY });

await mage.agents.trigger(

"ai-recommendations", { customer: "acme-corp" });

1

2

3

curl -X POST https://api.magemetrics.io/v1/agents/ai-recommendations/run \

-H "Authorization: Bearer $MM_KEY" \

-d '{"customer": "acme-corp"}'

1

2

3

<MageChat

apiKey={MM_PUBLIC_KEY}

theme={theme} />

Step 3

Call or embed

Chat UI, structured JSON, or raw data — you choose.

Hit the REST API for product features or internal tools. Use the SDK to plug into agent frameworks. Deploy a React component for end-user chat.

Multi-tenancy is built in — scope queries to users, accounts, or workspaces with a single parameter. White-label everything or use it headless.

Tasks

Integration options

1

2

3

const mage = new MageClient({ apiKey: MM_KEY });

await mage.agents.trigger(

"ai-recommendations", { customer: "acme-corp" });

1

2

3

curl -X POST https://api.magemetrics.io/v1/agents/ai-recommendations/run \

-H "Authorization: Bearer $MM_KEY" \

-d '{"customer": "acme-corp"}'

1

2

3

<MageChat

apiKey={MM_PUBLIC_KEY}

theme={theme} />

Step 3

Call or embed

Chat UI, structured JSON, or raw data — you choose.

Hit the REST API for product features or internal tools. Use the SDK to plug into agent frameworks. Deploy a React component for end-user chat.

Multi-tenancy is built in — scope queries to users, accounts, or workspaces with a single parameter. White-label everything or use it headless.

Tasks

Usage analytics

2,847

QUERIES

97.9%

RESULTS

QUALITY

+23

EXAMPLES

CURATES

Top queries

What are the top security risks for the Premium acc…

154 hits

Show me customer activity last week

134 hits

Find inactive users, last month

122 hits

Step 4

Ship and forget

We run the infra: caching, scaling, uptime.

The system learns from usage without you touching it. Want to fine-tune? Drop docs in the knowledge base. Want to debug? Query analytics show exactly what users ask.

No maintenance burden — just a layer that keeps getting better.

Tasks

Usage analytics

2,847

QUERIES

97.9%

RESULTS

QUALITY

+23

EXAMPLES

CURATES

Top queries

What are the top security risks for the Premium acc…

154 hits

Show me customer activity last week

134 hits

Find inactive users, last month

122 hits

Step 4

Ship and forget

We run the infra: caching, scaling, uptime.

The system learns from usage without you touching it. Want to fine-tune? Drop docs in the knowledge base. Want to debug? Query analytics show exactly what users ask.

No maintenance burden — just a layer that keeps getting better.

Pricing

No seats.
No meters.
No BS.

Flat-rate pricing with everything included.
Really, everything.

Custom flat-rate

Run a POC

Enterprise

Enterprise

Most teams launch for less than half the cost of one data hire.

Unlimited usage & users

Automate 3 core workflows

Deployed in under 30 minutes

Up to 5 AI agents

White-label embedding option

Standard integrations

BYOC deployment option

Basic analytics

Priority support & onboarding

Email & chat support

Testimonials

Real results. Real teams. Powered by AI.

“

The solution delivers beyond expectations. It is already making a real difference for our enterprise clients.

”

Irakli Menabde

CEO, REalyse

“

Overnight, we were able to add unlimited analytics options without slowing our roadmap or needing major engineering effort.

”

Dan Gianfreda

CEO, DeepStream

“

Our clients get AI-powered trade finance intelligence. We built it — Magemetrics gave us the layer to make it happen through light product integration, no large infrastructure project required.

”

Guy de Pourtalès

CTO, KomGo

“

Magemetrics provided the technical foundation and expertise that allowed us to ship a robust, scalable conversational analytics feature without reinventing the wheel.

”

Carlos Palminha

CTO, Covalo

“

The solution delivers beyond expectations. It is already making a real difference for our enterprise clients.

”

Irakli Menabde

CEO, REalyse

“

Our clients get AI-powered trade finance intelligence. We built it — Magemetrics gave us the layer to make it happen through light product integration, no large infrastructure project required.

”

Guy de Pourtalès

CTO, KomGo

“

Overnight, we were able to add unlimited analytics options without slowing our roadmap or needing major engineering effort.

”

Dan Gianfreda

CEO, DeepStream

“

Magemetrics provided the technical foundation and expertise that allowed us to ship a robust, scalable conversational analytics feature without reinventing the wheel.

”

Carlos Palminha

CTO, Covalo

The team

Repeat founders.
Seasoned engineers.
We've shipped the hard stuff.

SKIP THE SALES CALL

Talk to a founder

Book a slot

Founders still take every call here. Bring your hard questions, your "what about..." list, your skepticism.

You'll get straight answers on whether this actually fits — not a pitch.

The team

Repeat founders.
Seasoned engineers.
We've shipped the hard stuff.

SKIP THE SALES CALL

Talk to a founder

Book a slot

Founders still take every call here. Bring your hard questions, your "what about..." list, your skepticism.

You'll get straight answers on whether this actually fits — not a pitch.

FAQ

Still skeptical? Good.

Can't I just plug ChatGPT or MCP into my database?

You can — and it'll get you a demo. That's the easy 20%. Production is a different story. Without a semantic layer, every query starts from zero: no understanding of what your columns mean, how entities relate, or what 'active user' means in your business. You get inconsistencies, hallucinations, and every AI feature becomes a custom project that dies at data prep. The remaining 80% is why we exist — and we automate all of it. Self-configuring, live in hours, improving with every query.

What makes this different from BI tools?

What's the data setup and ongoing maintenance like?

How much control do we have over the experience?

How does this work with AI agents?

How accurate are the answers?

What's the external context thing?

Can we see what users are asking?

What is this going to cost us?

How do we know our data is safe?