Entende o contexto
Lê a operação, o cliente e o histórico antes de propor qualquer coisa.
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
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 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.
As áreas abaixo são partes da mesma operação, não produtos separados. Elas compartilham conta, permissões e histórico.
A inteligência artificial da Centriu participa da operação: entende contexto, prepara trabalho, executa rotinas e pede aprovação quando importa.
Lê a operação, o cliente e o histórico antes de propor qualquer coisa.
Redige, organiza, calcula e deixa pronto para revisão humana.
Roda o que é repetitivo dentro dos limites definidos pela empresa.
Cruza áreas, identifica prioridade e mostra o motivo da recomendação.
O que é sensível passa por uma pessoa antes de valer. Sem exceção silenciosa.
Registra o que aconteceu e usa o resultado para melhorar a próxima decisão.
Uma plataforma, várias frentes de trabalho. Tudo no mesmo contexto, com a IA participando do que dá para acelerar.
CRM, pipeline, oportunidades, propostas, follow-up e automações.
WhatsApp, Instagram, Messenger, chat do site e e-mail no mesmo contexto.
Tarefas, responsáveis, prazos, aprovações, agenda e capacidade.
Contas, cobranças, caixa, fiscal, margem, IR, orçamento e inteligência econômica.
Planejar, produzir, aprovar, publicar e medir conteúdo e campanhas.
Painéis, alertas, previsões, recomendações e leitura executiva.
Rotinas executadas continuamente pela IA com controle e aprovação.
Diagnóstico, estratégia, transformação, acompanhamento e especialistas.
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 funcionandoA Centriu combina tecnologia, inteligência, método e acompanhamento. A consultoria diagnostica, desenha, implanta e acompanha — com evidências, não com apresentação.
Diagnóstico e imersão na operação
Estratégia e prioridades
Roadmap de transformação
Desenho da arquitetura operacional
Implantação conduzida
Acompanhamento com evidências
Benchmarking e leitura de mercado
Especialistas, rede e inteligência coletiva
Uma conversa para entender onde a sua operação perde tempo, dinheiro ou capacidade — e o que a Centriu faria primeiro.
problema
At the time a new AI-agent tool suite was being built for Centriu Vesper (2026-09-02), a direct measurement of the system's own funnel found 123 strategic insights sitting in pending status. Also, 48 execution tasks were still open. Both were described in the rollout's own documentation as stalled for months. The tools built to work through it are deliberately narrow. They do not sweep through that backlog in bulk. An insight can only be marked `applied` or `dismissed`, one at a time. It is never deleted, no matter which way it goes. The decision itself becomes the permanent record. A task can only be marked complete for a task that genuinely belongs to the requesting organization. It also cannot be already closed. The tool's own catalog documentation carries an explicit, plainly-stated instruction: only mark as done what was actually done. There is no operation anywhere in the suite that closes more than one item per call.

A queue of ideas or tasks that nobody has touched in months is just a sign of limited time and competing priorities. The moment something capable of acting on that queue quickly is introduced, a second and different risk appears. This could be a script, an automation, or an AI agent. This risk is the temptation, or the accidental capability, to clear the backlog all at once. This is instead of working through it with the same judgment a person would have applied one item at a time. A queue cleared in bulk can look identical, from the outside, to one genuinely triaged. This is true until someone asks what happened to a specific idea or task. Then they find no real record of a decision being made about it.
A queue of ideas or tasks that nobody has touched in months is just a sign of limited time and competing priorities. The moment something capable of acting on that queue quickly is introduced, a second and different risk appears. This could be a script, an automation, or an AI agent. This risk is the temptation, or the accidental capability, to clear the backlog all at once. This is instead of working through it with the same judgment a person would have applied one item at a time. A queue cleared in bulk can look identical, from the outside, to one genuinely triaged. This is true until someone asks what happened to a specific idea or task. Then they find no real record of a decision being made about it.
The rollout's own training material states the measured backlog directly. It does not soften it. There are 123 insights and 48 tasks, both stalled for months. This is framed explicitly as something to work through "with judgment, not in bulk." That framing shows up as a real limit in how the tools were actually built. It is not just a stated intention.
The insight-triage tool accepts exactly one insight identifier and exactly one decision per call. This is mapped from either Portuguese or English input down to one of two fixed outcomes: applied or dismissed. There is no argument anywhere in the tool's signature that accepts a list, a range, or an "all pending" flag. Clearing all 123 would require 123 separate, individually-decided calls. Each one is scoped to the requesting organization. So an agent can only triage insights that actually belong to it. Once triaged, the insight is not deleted. Its status changes. It remains queryable as part of the project's own history. This means the funnel's total count and the number of decisions actually made can always be compared against each other.
The task-completion tool is built the same way. It takes a single task identifier. It checks that the task belongs to the requesting organization. It also checks that it is not already marked complete. Then it marks it done. Its own catalog entry states the guardrail in plain language. This is the documentation a calling AI agent reads before deciding how to use it. It says: only conclude what was genuinely done. That line exists specifically because a task-completion tool has an unusually easy failure mode. This is unlike most read-only tools. An agent asked "did you finish the follow-up tasks" has an obvious reason to report success. A tool with no explicit instruction against premature or unconfirmed closure leaves that judgment call entirely to the model's own behavior in the moment. It does not limit it structurally.
An insight-triage tool takes one insight identifier and one decision (applied or dismissed) per call. No bulk or "all pending" operation exists anywhere in the suite.
A task-completion tool takes one task identifier per call. It is scoped to the requesting organization. It is also scoped to tasks not already marked complete. Its own documentation instructs against marking anything done that wasn't genuinely done.
Neither an insight nor a task is ever deleted by these tools. A triaged insight keeps its decision as a permanent, queryable record. A completed task keeps who completed it and when.
A separate panorama tool shows the current pending-insight and open-task counts per client project. So the size of the queue is visible before anything is acted on.
Confirmed today via direct inspection: neither tool accepts a list, a range, or a bulk flag of any kind. Every call is scoped to exactly one record.
An AI agent can now work through Centriu Vesper's stalled insight and task backlogs one explicit, recorded decision at a time. This closes a real, measured gap between a queue everyone could see and a mechanism actually built to work through it. It does this without introducing the bulk-clearing shortcut. That shortcut would have made the backlog's reported size meaningless.
An AI agent can now work through Centriu Vesper's stalled insight and task backlogs one explicit, recorded decision at a time. This closes a real, measured gap between a queue everyone could see and a mechanism actually built to work through it. It does this without introducing the bulk-clearing shortcut. That shortcut would have made the backlog's reported size meaningless.
A backlog of 123 pending insights could be reduced to zero. This could happen by a script that marks every single one "dismissed" without reading any of them. This would be a technically complete queue that represents no actual judgment. Centriu's tool suite cannot do that. Reaching zero requires 123 individual decisions. Each one is recorded against the specific insight it applied to.

123 pending insights and 48 open execution tasks. Both were stated in the rollout's own documentation as stalled for months at the time (2026-09-02). This was a measured snapshot, not a live count.
No. There is no bulk operation anywhere in the suite. Every insight and every task requires its own separate, individually-decided call.
It is marked applied or dismissed. It is kept as a permanent, queryable record. It is never deleted.
The task-completion tool's own documentation states the rule explicitly. It says: only mark as done what was genuinely done. The tool is structurally limited to one task per call. This makes a false bulk claim of completion impossible.
No. The decision (applied or dismissed) is made by whoever or whatever is doing the triaging. The tool records that decision. It does not make it.
It is sold with tiered levels (Starter/Pro/Max). Exact current values are on the central pricing page.
At the time a new AI-agent tool suite was being built for Centriu Vesper (2026-09-02), a direct measurement of the system's own funnel found 123 strategic insights sitting in pending status. Also, 48 execution tasks were still open. Both were described in the rollout's own documentation as stalled for months. The tools built to work through it are deliberately narrow. They do not sweep through that backlog in bulk. An insight can only be marked `applied` or `dismissed`, one at a time. It is never deleted, no matter which way it goes. The decision itself becomes the permanent record. A task can only be marked complete for a task that genuinely belongs to the requesting organization. It also cannot be already closed. The tool's own catalog documentation carries an explicit, plainly-stated instruction: only mark as done what was actually done. There is no operation anywhere in the suite that closes more than one item per call.