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.

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

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.

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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.

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

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

AI Cost Anomaly Detection and Invoice Reconciliation Automation: An Unknown Cost Is Never Recorded as Zero

A cost-tracking system that quietly turns "we couldn't calculate this" into a zero is lying by omission. It lies in a dangerous direction: underestimating what was actually spent. Centriu TrustOps refuses that shortcut. An unrecorded cost is stored as an explicit null with its own status. It is never folded into a total as if it were nothing. On top of that honest foundation sits real anomaly detection. It comes from two distinct and reproducible families: fixed rules (a charge after a service was suspended, a discontinued model still in use, a duplicate charge) and a statistical method built on the median and a strong measure of spread rather than the average. This is done so a single cost spike cannot corrupt the very baseline used to detect it. Vendor invoices are reconciled through a two-step, human-confirmed process. This includes a SHA-256 hash on the file and a check of the declared total against the sum of its own line items.

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Why summing unknowns as zero is the most expensive mistake a cost system can make

Every cost-tracking system eventually hits a gap it cannot fill. This can be a usage event with no matching price, a currency with no exchange rate for that date, or a vendor line item that does not map cleanly to a category. The tempting shortcut is to treat the gap as zero and move on. A total that includes a zero still looks like a complete, confident number. That confidence is exactly the problem. A total built partly from zeros that are actually unknowns is a total that systematically understates real spend. Nobody double-checks a bill that looks smaller than expected. The gap does not announce itself. It quietly erodes the number everyone trusts.

Every cost-tracking system eventually hits a gap it cannot fill. This can be a usage event with no matching price, a currency with no exchange rate for that date, or a vendor line item that does not map cleanly to a category. The tempting shortcut is to treat the gap as zero and move on. A total that includes a zero still looks like a complete, confident number. That confidence is exactly the problem. A total built partly from zeros that are actually unknowns is a total that systematically understates real spend. Nobody double-checks a bill that looks smaller than expected. The gap does not announce itself. It quietly erodes the number everyone trusts.

Quero resolver isso

How Centriu TrustOps detects anomalies and reconciles invoices honestly

A cost that cannot be calculated is recorded explicitly as null with its own calculation-method status. It is never silently treated as zero in any total. A database constraint makes it impossible to fake a different origin for that value. The type system used to represent money propagates the gap rather than hiding it. Anomaly detection runs on two separate, reproducible families. The rule-based family checks deterministic conditions. These include cost continuing after a service was suspended, a discontinued model still generating charges, a duplicate charge, and usage outside a declared time window. The statistical family compares a scope's current cost against its own historical baseline. It uses a strong z-score built on the median and the median absolute deviation rather than the mean and standard deviation. This is done deliberately because a single genuine spike distorts a mean and a standard deviation immediately. This would blunt the very detector meant to catch that spike. The median and its strong spread measure resist that distortion. Every finding from either family carries a confidence value. This is explicitly documented as a measure of how well the evidence supports the finding, not a probability of fraud. Every anomaly is explainable line by line. An anomaly has to be explainable to become an investigation, a chargeback, or an invoice dispute. Vendor invoices move through a genuine two-step process with human confirmation at the center. The file is received, its MIME type and byte-level signature are validated. A SHA-256 hash is recorded. The content is extracted and previewed ten lines at a time. A column mapping is suggested, and the system checks for a duplicate period. Only once a person confirms the mapping is the same file resubmitted. It is re-hashed on the server to confirm it has not changed. Only then does it create the invoice and its line items. It validates that the declared total matches the sum of what was actually itemized.

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What is actually built today

Costs that cannot be calculated are recorded as explicit nulls with their own status. They are never folded into a total as zero. This is enforced by a database constraint, not just application logic.
Two independent, reproducible anomaly-detection families exist. These are deterministic rules (post-suspension charges, discontinued-model usage, duplicate charges, off-hours usage) and a statistical method using median and median absolute deviation. This is specifically to resist distortion from the very spikes it is meant to catch.
A confidence value is on every anomaly finding. It is explicitly documented as a measure of evidence strength rather than a probability of fraud.
A two-step, human-confirmed invoice import exists. This includes MIME and byte-signature validation, a SHA-256 hash, a ten-line preview with a suggested column mapping and duplicate-period detection. This is followed by a re-hashed confirmation submission before the invoice and its line items are actually created.
A check exists that a confirmed invoice's declared total matches the sum of its own line items before it is accepted.
Cost is immutable once confirmed, invoiced, or reconciled. A correction is recorded as a new, linked delta event pointing at the original. It is never an edit to it.
A pending currency conversion never enters a cost total. A later exchange rate is never applied to convert an earlier cost. Only a rate dated on or before the cost's own date is used.
Twenty-four dedicated financial-tracking tables exist. All have row-level isolation by organization. None of them have a delete policy. Financial history is never erased.

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What changes operationally

The structural change is that gaps in cost data stay visible as gaps. They do not quietly become zeros that understate real spend. A genuine cost spike gets caught by a method built specifically to resist being fooled by the spike itself. Invoice entry gets a real integrity check. This includes a hash, a validated mapping, and a total that has to match its own line items. This is instead of trusting a manually keyed number. Centriu attaches no figure to what this catches. It depends entirely on an organization's AI spend volume and how many vendors and cost categories it reconciles.

The structural change is that gaps in cost data stay visible as gaps. They do not quietly become zeros that understate real spend. A genuine cost spike gets caught by a method built specifically to resist being fooled by the spike itself. Invoice entry gets a real integrity check. This includes a hash, a validated mapping, and a total that has to match its own line items. This is instead of trusting a manually keyed number. Centriu attaches no figure to what this catches. It depends entirely on an organization's AI spend volume and how many vendors and cost categories it reconciles.

Quero esses resultados

A statistical outlier and a bad invoice surface the same week (illustrative scenario, not a real client)

A specific project's daily AI cost has held steady for months. One day it jumps sharply. A simple average-based check would have already absorbed part of that jump into a rising baseline. This would happen over the prior few days of gradual increase leading up to it. The median-based method does not do this. The jump has not yet had time to drag a median that is resistant to that kind of outlier. The anomaly fires with a documented confidence level and a specific comparison. This is today's cost against the recent median, with the deviation stated in plain terms. A reviewer traces it to a misconfigured process retrying the same expensive call in a loop. They catch it the same day rather than at the end of the billing cycle.

Separately, a vendor invoice is uploaded for that same period. The system validates the file, hashes it, and shows a ten-line preview with a suggested mapping. A reviewer confirms it. On resubmission, the file is re-hashed and matches. The invoice is created. The declared total on the invoice does not match the sum of its line items by a few cents. This is likely a rounding difference on the vendor's side. The mismatch is flagged rather than silently accepted. The reconciliation is held until it is resolved rather than posted with an unexplained gap.

A statistical outlier and a bad invoice surface the same week (illustrative scenario, not a real client)

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How to start

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Frequently asked questions

What happens to a cost that cannot be calculated?

It is recorded as an explicit null with its own status. It is never silently treated as zero in a total. A database constraint enforces this. It cannot be worked around by writing to a different field.

Why use the median instead of the average to detect a cost spike?

Because a genuine spike distorts an average and its standard deviation immediately. This blunts detection of the very spike it is supposed to catch. The median and a strong spread measure resist that distortion.

Does a high confidence score mean fraud was detected?

No. Confidence measures how well the evidence supports the finding. This is explicitly documented as distinct from a probability of fraud. A human always reviews the finding.

How is a vendor invoice actually processed?

In two steps. The file is validated and hashed with a preview and suggested mapping shown first. Only after a person confirms that mapping is the file resubmitted. It is re-hashed and turned into an actual invoice with its line items.

What happens if an invoice's declared total does not match its line items?

The mismatch is flagged rather than silently accepted. The reconciliation is held until it is resolved.

Can a confirmed cost record be edited later?

No. A correction is written as a new, linked delta event pointing at the original record. The original record is never edited or deleted.

What does Centriu TrustOps cost?

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

Ainda tenho dúvida

See how Centriu TrustOps detects AI cost anomalies

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