For companies with complex operations

AI agents that operate inside your systems

AI to truly organize and automate your company's operations. Connected to your warehouse, your repository and your tools: they query real data, open pull requests, run tests, launch campaigns and orchestrate complete flows — with traceability for every action.

✓ On your infrastructure✓ Every action auditable✓ Pilot before rollout
Who is it for?

When the work no longer fits in a chatbot

Your data lives in a warehouse

Snowflake, BigQuery or Cloud SQL with the truth of the business inside — and every question from the team goes through an analyst.

Your engineering team is saturated

The backlog fills up with repetitive tasks: migrations, tests, refactors and fixes nobody wants to pick up.

Your operation spans many systems

CRM, ERP, helpdesk and ads that don't talk to each other, and someone stitches them together by hand every morning.

Marketing and content at scale

Hundreds of pages, campaigns and keywords that need optimizing and reporting every week.

Capabilities

They don't answer: they execute

Every agent has defined permissions, assigned tools and a record of everything it did.

They query your real data

Connected to Snowflake, Cortex, BigQuery or Cloud SQL. They answer with the figure from your warehouse, not an estimate.

They understand your code and open PRs

They read the repository, propose the change and open the pull request or merge request for your team to review.

They run tests in the browser

Real unit and flow tests in Chrome: they navigate your product, detect the failure and report with evidence.

They analyze and chart instantly

Ask about the quarter's sales and it returns the analysis with the chart ready, without waiting on anyone.

They review contracts in real time

They read the contract as you upload it, flag risk clauses and cite where each observation came from.

They monitor your applications

They watch your services, detect the failure, try to recover it on their own and alert you with the diagnosis done.

They build ML models

From training to deployment: advanced models in production, versioned and monitored.

They send reports on their own

Yesterday's report lands at 7 am by email or Slack, with the number, the variation and what caused it.

They orchestrate several agents

One agent coordinates the rest: distributes tasks, waits for results and decides the next step in the flow.

Orchestration

One flow, several agents, a single panel

This is what a real flow looks like from start to finish — every step is logged and reversible.

  1. Trigger

    A branch's margin drops

    The agent detects the anomaly in the warehouse without anyone asking.

  2. Diagnosis

    Cross-references sales, costs and campaigns

    It queries several sources and finds that one campaign's CPA tripled.

  3. Action

    Pauses the campaign and opens the PR

    It executes what it's allowed to and leaves what requires human approval in review.

  4. Close

    Reports to the decision-maker

    It sends the summary with the cause, what it did and what's awaiting approval.

Integrations

They connect to what you already have

No stack migration. The agent comes in with its own credentials and minimal permissions.

Data

  • Snowflake · Cortex
  • Cloud SQL
  • BigQuery · dbt
  • Postgres · Redshift

Code

  • GitHub · GitLab
  • CI/CD pipelines
  • Playwright · Chrome
  • Jira · Linear

Models and cloud

  • GCP Vertex AI · Cortex
  • OpenAI · Anthropic
  • AWS · Azure
  • Vector DBs · RAG

Business

  • CRM · ERP
  • WhatsApp Business API
  • Google & Meta Ads
  • Slack · email
What they run on

Built on GCP and Snowflake

We don't start from scratch or sell you a generic license. Each agent is built to measure on proven enterprise infrastructure and connects directly to your data.

Google Cloud

Where the agent runs: Vertex AI for the models, Cloud Run to execute and IAM so it only touches what you authorize.

Snowflake

Where your data lives: the agent queries with Cortex on your own warehouse, with access governed per user.

Your custom layer

On top goes what's yours: your data sources, your business rules, your repositories and your approval limits.

Success stories

Agents already running in production

No client names — just the challenge, what we built and the number.

Applied AI · legal

AI legal assistant for the legal department of a multinational

Challenge · the legal team reviewed contracts and corporate documents by hand.

Several specialized agents —contracts, corporate documents, advisory and meetings— answer based on the company's documents, with search redesigned for long documents.

Result
From 100% to 20%
of answers validated by hand: the sampling compliance asked for.
Vertex AI (Gemini)RAGMulti-agentFastAPITerraform
Applied AI · data

Conversational data assistant for a global information company

Challenge · the business depended on engineering for every data query.

Natural-language questions on the data warehouse with governed access, an admin panel —tokens, observability, alerts— and automatic evaluations before every deployment.

Result
Analytics without SQL
for non-technical users, with dev → prod promotions without downtime.
Snowflake CortexSemantic ViewsNext.jsCI/CD
Our own case · Rankea

Agents running a complete digital business

Agents on WhatsApp, Slack and email that generate and publish content, monitor infrastructure and self-recover, prepare reports and handle team requests — always with human approval before any external action.

Result
2 people
run 3 weekly LinkedIn posts, a daily reel and carousel, daily blogs across two SEO silos and automated reports.
Multichannel agentsContentAutomationMonitoring

Want the technical detail of one of them? See more cases in IT & AI →

Governance and security

Autonomy, but with control

Permissions per agent

Each one only sees and touches what its role allows.

Auditable log

What it did, when and with which data. All queryable.

Human approval

Sensitive actions stay in review; they don't run on their own.

Your data stays in

They run in your cloud and never train public models.

Implementation

Pilot first. Rollout later.

  1. 1

    Technical discovery

    We review your sources, permissions and the case that hurts most. At no cost.

  2. 2

    Pilot of one flow

    One agent, one measurable case, in a controlled environment with agreed metrics.

  3. 3

    Rollout by area

    We add flows and teams in stages, with clear permissions and limits.

  4. 4

    Operation and improvement

    Monitoring, tuning of prompts and tools, and support with SLA.

Commercial model

It depends on your systems, so we define it together

The proposal comes out of the technical discovery — which costs nothing and commits you to nothing.

Technical discovery
Free

A session with your technical team to pick the first flow and estimate the effort.

  • Review of sources and permissions
  • Prioritized use case
  • Written proposal
Book a session
Continuous operation
Ask usvolume-based monthly fee

Several agents in production, monitored and improved every sprint.

  • New flows in stages
  • Support with SLA
  • Monthly impact report
Quote operation

A smaller business, just customer service and sales on WhatsApp? See AI agents for businesses →

Frequently asked questions

What your technical team asks

Does the data leave our infrastructure?

It doesn't have to. The agent runs in your cloud with its own credentials and minimal permissions, and never trains public models with your information.

Can it execute something without our approval?

Only what you authorize. Everything else stays in review — that's why it opens PRs instead of merging, and leaves the proposed change for a human to decide.

What if it hallucinates a number?

It doesn't answer from memory: it queries the source and cites where the number came from. If the query fails, it says so instead of making something up.

Does it lock us into a model provider?

No. We work on Vertex, OpenAI, Anthropic or your own models, and the agent can switch engines without rebuilding the flow.

How long does the pilot take?

Weeks, not months. Discovery happens this week and the pilot starts as soon as we have access and the case defined.

Your operation doesn't need this level yet? If what you're after is an AI virtual assistant that answers WhatsApp, quotes and books appointments, start with AI agents for businesses →

Free technical discovery · reply within 24 h

Bring your most expensive flow and we'll tell you if an agent solves it

A session with your technical team. If we don't see a case, we'll tell you — we'd rather do that than sell you a pilot that doesn't pay off.

Book a technical demo

We reply the same day.

🔒 We sign an NDA before looking at any system