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Para empresas que querem crescer com controle

Um sistema para operar sua empresa com IA.

Vendas, marketing, atendimento, operação, financeiro e inteligência trabalhando sobre o mesmo contexto — para sua empresa ganhar escala sem perder controle.

Sua empresa inteira. Uma operação. IA trabalhando.

Para empresas de qualquer setor que querem crescer com estrutura, controle e inteligência.

Painel ilustrativo do Sistema Centriu com sete frentes trabalhando: atendimento, comercial, operação, agentes, inteligência, conteúdo e marketing. Cada frente mostra o trabalho concluído ou o próximo passo.

Representação ilustrativa do trabalho em execução

O problema

Sua empresa não deveria operar em pedaços

Não é falta de ferramenta. É que cada ferramenta resolve um pedaço, e ninguém é dono do todo. O custo disso não aparece numa fatura — aparece no mês seguinte.

  • Sistemas que não se falam

    O mesmo dado é digitado de novo — e cada cópia conta uma história diferente.

  • Dados duplicados

    Ninguém sabe qual versão é a verdadeira na hora de decidir.

  • Conversas perdidas

    O cliente repete o contexto a cada canal e a cada pessoa.

  • Tarefas espalhadas

    O trabalho vive em planilhas, mensagens e na memória de alguém.

  • Decisões sem contexto

    A escolha é feita com o recorte que estava à mão, não com o que importava.

  • Automações desconectadas

    Cada ferramenta automatiza um pedaço e ninguém enxerga o todo.

Nenhum desses problemas se resolve comprando mais um software. Eles se resolvem quando a operação inteira passa a trabalhar sobre o mesmo contexto.

A resposta

Tudo trabalha sobre o mesmo contexto.

A Centriu não é uma coleção de produtos. É uma plataforma em que clientes, áreas e agentes leem e escrevem no mesmo lugar.

Cliente 360

Um contexto, não vários cadastros

Cada conversa, tarefa, campanha, cobrança e decisão fica ligada ao cliente e à operação — não a um sistema isolado.

  • Clientes
  • Comercial
  • Atendimento
  • Operação
  • Financeiro
  • Marketing
  • Inteligência
  • Agentes
  • Consultoria

As áreas abaixo são partes da mesma operação, não produtos separados. Elas compartilham conta, permissões e histórico.

IA que trabalha — não um chatbot ao lado

A inteligência artificial da Centriu participa da operação: entende contexto, prepara trabalho, executa rotinas e pede aprovação quando importa.

Entende o contexto

Lê a operação, o cliente e o histórico antes de propor qualquer coisa.

Prepara o trabalho

Redige, organiza, calcula e deixa pronto para revisão humana.

Executa rotinas

Roda o que é repetitivo dentro dos limites definidos pela empresa.

Recomenda a próxima ação

Cruza áreas, identifica prioridade e mostra o motivo da recomendação.

Pede aprovação

O que é sensível passa por uma pessoa antes de valer. Sem exceção silenciosa.

Mantém histórico e aprende

Registra o que aconteceu e usa o resultado para melhorar a próxima decisão.

O que a Centriu faz

Uma plataforma, várias frentes de trabalho. Tudo no mesmo contexto, com a IA participando do que dá para acelerar.

Comercial

CRM, pipeline, oportunidades, propostas, follow-up e automações.

Atendimento

WhatsApp, Instagram, Messenger, chat do site e e-mail no mesmo contexto.

Operação

Tarefas, responsáveis, prazos, aprovações, agenda e capacidade.

Financeiro

Contas, cobranças, caixa, fiscal, margem, IR, orçamento e inteligência econômica.

Marketing

Planejar, produzir, aprovar, publicar e medir conteúdo e campanhas.

Inteligência

Painéis, alertas, previsões, recomendações e leitura executiva.

Agentes

Rotinas executadas continuamente pela IA com controle e aprovação.

Consultoria

Diagnóstico, estratégia, transformação, acompanhamento e especialistas.

Para quem é

Para empresas que querem crescer — e crescer certo.

A Centriu faz sentido quando o volume aumenta e a estrutura precisa acompanhar. Não é sobre setor nem tamanho: é sobre a operação conseguir sustentar o próximo estágio.

As vendas crescem, mas o processo não acompanha.

As áreas trabalham separadas e o cliente sente.

A operação depende de pessoas específicas.

O financeiro ficou complexo e o caixa perde visibilidade.

O atendimento cresce em volume e em canais.

A IA entra sem contexto, controle ou histórico.

Se a empresa ainda não começou a crescer, a Centriu também ajuda a preparar a estrutura para o primeiro salto.

Ver a Centriu funcionando
Consultoria

Tecnologia sozinha não resolve uma operação mal desenhada.

A Centriu combina tecnologia, inteligência, método e acompanhamento. A consultoria diagnostica, desenha, implanta e acompanha — com evidências, não com apresentação.

A participação de especialistas depende da solução e do contrato. Não é um item incluído automaticamente em toda contratação, e não prometemos acompanhamento humano ilimitado.

Veja a Centriu funcionando na sua operação

Uma conversa para entender onde a sua operação perde tempo, dinheiro ou capacidade — e o que a Centriu faria primeiro.

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problema

E-commerce Event Ingestion Integrity Automation: Zero Events, Since the Pipeline Existed

Centriu Flow's store-event ingestion endpoint sent a store event's name and category using field names that did not match the real database columns. Every insert was rejected by the database with a standard error. Almost nothing in the calling code checked that response. The screen reported success while nothing was written. The result: not one real e-commerce event was recorded since this ingestion path existed. This means every automation depending on a store event — an abandoned-cart follow-up, a post-purchase sequence — never fired for any store connected through this pipeline. The fix corrects the two field names to match the real schema. It adds an automated gate that compares every insert's field list against the database's live schema snapshot. This way, the same defect cannot ship silently again. A direct production probe after the fix confirmed a real event now lands in the table. Its daily counter increments.

E-commerce Event Ingestion Integrity Automation: Zero Events, Since the Pipeline Existed

A write that fails with an error nobody was reading

A database rejecting an insert because a column name does not exist is a loud error. The problem is not the error's volume. It is whether anything downstream is listening for it. When a calling function fires the write and moves on without checking the response, a rejected insert and a successful one look the same. They look identical from every point a person or a dashboard would check: the request completed, the screen advanced, the log stayed quiet. The only place the truth lived was the one table nobody was querying directly.

  • A database rejecting an insert because a column name does not exist is a loud error. The problem is not the error's volume. It is whether anything downstream is listening for it. When a calling function fires the write and moves on without checking the response, a rejected insert and a successful one look the same. They look identical from every point a person or a dashboard would check: the request completed, the screen advanced, the log stayed quiet. The only place the truth lived was the one table nobody was querying directly.

How a schema-comparison gate found what tests could not, and what the production probe confirmed

The store-event ingestion function sent two fields under names that made sense on their own. It sent a bare name for the event and a bare category for it. But the actual table storing these events uses more specific column names for both. Because the database enforces its schema strictly, PostgREST rejected every one of these inserts. The calling code checked almost none of these responses. So the rejection was invisible from every angle except the one table that should have been filling up with rows and never did.

The defect was found by building something neither a test suite nor a typecheck could provide. It was a direct, automated comparison between what the code tries to write and what the live database schema allows. A snapshot of every real table's real column list was pulled directly from the database's own information schema. This was not from any file describing an intended design. It became the source of truth a dedicated check runs every insert and upsert against. Proving the check works meant deliberately reintroducing the original wrong field name. It confirmed the check turns red because of that mismatch, not by coincidence.

Once the two field names were corrected to match the real table, a direct production probe confirmed the fix. It was not just an assertion: a real, live event was sent through the same ingestion path. It was measured landing in the actual table. The table's own daily event counter incremented by exactly one in response. That confirmation matters because the entire original defect was invisible from every layer except the database's own state. The same discipline that found the bug is what closes the loop on the fix.

What is actually built today

  • Centriu Flow's store-event ingestion endpoint writes using the correct, real column names for a store event's name and category. This is verified against the live database schema.

  • A dedicated automated gate compares every database insert and upsert in the codebase against a snapshot of the real, live schema. This is pulled directly from the database's own information schema — not from a file describing an assumed design.

  • The schema snapshot is meant to be regenerated after every migration. This keeps the comparison current rather than checking against a schema that can drift out of date.

  • The gate is proven by mutation. Deliberately reintroducing a wrong field name turns the check red because of that mismatch. This confirms the check tests the right thing rather than passing by coincidence.

  • A direct production probe, run after the fix shipped, confirmed a real event lands in the correct table. Its daily counter increments — verification against the live system, not just against a test double.

What changes operationally

Store events sent through Centriu Flow's ingestion path are now written under the correct column names. They are verified against the live database schema before shipping. This closes a gap where zero e-commerce events had ever been successfully recorded since the pipeline existed. Every automation depending on one had never fired.

  • Store events sent through Centriu Flow's ingestion path are now written under the correct column names. They are verified against the live database schema before shipping. This closes a gap where zero e-commerce events had ever been successfully recorded since the pipeline existed. Every automation depending on one had never fired.

An abandoned-cart automation, correctly configured, waiting for an event that never came (illustrative framing of the actual measured finding)

A store connects its checkout flow to Centriu Flow. It configures an automation to follow up whenever a cart is abandoned. The automation itself is set up correctly, active, and ready. Before the fix, the event meant to trigger it is sent to the ingestion endpoint. It is rejected by the database and silently discarded. The automation never receives a single trigger. Nothing about its own configuration reveals why. After the fix, the identical abandoned-cart event is written successfully. The store's daily event count reflects it. Whether a journey then starts is a separate link. In the current code, a recorded store event does not yet start a Flow journey — only a submitted form does.

An abandoned-cart automation, correctly configured, waiting for an event that never came (illustrative framing of the actual measured finding)

How to start

Frequently asked questions

Why did event ingestion fail with no visible error?

The database rejected every insert outright because the field names did not match its real columns. The calling code did not check that rejection. So the request appeared to succeed from every angle except the database's actual state.

How long had this been broken?

Since the ingestion path first existed, the measured finding was that zero real e-commerce events had ever been successfully recorded through it.

How was the fix actually verified, not just asserted?

A direct production probe sent a real event through the corrected path. It confirmed it landed in the real table. The table's own daily counter incremented by exactly one.

What stops this class of defect from happening again?

A dedicated automated gate now compares every database write in the codebase against a live snapshot of the real database schema. It is proven by deliberately reintroducing a wrong field name and confirming the gate catches it.

What does Centriu Flow cost?

It is sold by subscription with a published starting price. Exact current values are on the central pricing page.

See how Centriu Flow verifies every store event actually gets recorded

Centriu Flow's store-event ingestion endpoint sent a store event's name and category using field names that did not match the real database columns. Every insert was rejected by the database with a standard error. Almost nothing in the calling code checked that response. The screen reported success while nothing was written. The result: not one real e-commerce event was recorded since this ingestion path existed. This means every automation depending on a store event — an abandoned-cart follow-up, a post-purchase sequence — never fired for any store connected through this pipeline. The fix corrects the two field names to match the real schema. It adds an automated gate that compares every insert's field list against the database's live schema snapshot. This way, the same defect cannot ship silently again. A direct production probe after the fix confirmed a real event now lands in the table. Its daily counter increments.