# Service as a Software: your customer receives the finished work | Tog Lab > Instead of selling access to a tool, the company delivers the result: the report, the dashboard, the resolved ticket. AI agents run the repetitive tasks, one by one, and people on the team check them, make the decisions and are accountable for what is delivered. URL: https://www.toglab.co/en/service-as-a-software.html [Português do Brasil](https://www.toglab.co/pt-br/service-as-a-software.html.md) · [Português de Portugal](https://www.toglab.co/pt-pt/service-as-a-software.html.md) · [Español](https://www.toglab.co/es/service-as-a-software.html.md) · [Italiano](https://www.toglab.co/it/service-as-a-software.html.md) [Services](https://www.toglab.co/en/servicos.html) Service as a Software # Service as a Software: your customer receives the finished work [Talk to us](https://www.toglab.co/en/contato.html) Compare with the traditional model People on the teamCheck, decide and are accountable for the result AI agentsCarry out the repetitive work within the rules SaaS, ERP and dataThe tools the company already has ## From SaaS to Service as a Software What companies buy in software has changed: the hours of the people doing the work, the tool license, the task done by an agent and, finally, the whole service delivered. All four models coexist in the same company. In the last two models, AI and people work together: the agents do the work, and people on the team check, adjust and approve it before it reaches the customer. ## Task as a Service: the agent runs the task Task as a Service means buying the task done, one at a time: reconciling a transaction, answering a ticket, logging a field visit. AI agents carry it out within your business rules, a person steps in when the task falls outside the standard, and you pay for what was completed. A Service as a Software deliverable is made of many tasks. That is why Task as a Service is often the first step: start with a task that repeats a lot, measure the result, then combine the tasks into a complete service. Task as a Service You buy each completed task. Service as a Software You buy the whole service, made of those tasks. Example deliverableThe monthly analysis, ready for the business owner Each line is a task that can be bought on its own. Together, they make up the service. ## The traditional model and the agent model Pick a task and see what changes when agents run it and a person is accountable for the result. A person is accountable for every task Before anything starts, what each agent can read, change and send is defined in writing. Cases outside the rules stop and wait for a person to decide. Everything is logged: the source data, the rule applied and who approved it. [How governance works](https://www.toglab.co/en/ai-accelerated.html#governanca) [Read the article on Task as a Service](https://www.toglab.co/en/insights-task-as-a-service.html) [Assess a task in my business](https://www.toglab.co/en/contato.html) ## SaaS stays at the foundation Agents operate the tools the company already has and deliver the result. The license still holds the data, the rules and the history. For companies that sell SaaS, this layer becomes a new offering on top of the same product: beyond access, the customer can buy the work already done. ## Examples by business area We always start with the same question: what deliverable does your customer recognize and agree to pay for? We call that deliverable the unit of value. See how it looks in a few areas. Each company’s design comes from understanding the process with the people who do the work day to day. ## Where we are already applying it With clients and in Tog Lab’s own products. Each card shows the model. ## Further reading ## Superintelligence: what happened in September 2026 On Sep 22, 2026, at the UN General Assembly, the President of the United States announced the switch from “artificial intelligence” to “super intelligence” (source: Miller Center). On Sep 29, 2026, the executive order “Inaugurating the Era of Super Intelligence” directed US federal agencies to use “SI” instead of “AI”. The change is one of terminology and does not change the law (source: White House fact sheet). Model capabilities will keep rising. The work now is deciding where they fit in the business, with which data, under which rules and who is accountable for the result. [Read more in Insights](https://www.toglab.co/en/insights.html) ## Let’s find your business’s unit of value Someone from business and someone from engineering on our team will reply within 1 business day. [Talk to us](https://www.toglab.co/en/contato.html) [hello@toglab.co](mailto:hello@toglab.co) ## More on this page - Collect bank statements, invoices and transactions - Reconcile each transaction with its invoice - Flag discrepancies and anything missing - Decide the cases outside the rules — p - Build indicators, alerts and scenarios - Review and talk it through with the business owner — p - Someone in finance, one transaction at a time — Agents that read statements and invoices and reconcile each transaction - At month-end close, in a batch, a few days after the month ends — Throughout the month, as the data comes in - In all of the work, including the repetitive parts — On discrepancies and on approving the close - Spreadsheets and email threads — Each reconciliation with its source, the rule applied and who approved it - Team hours or per-user licenses — Per reconciled transaction or per company served - Support reps answer every message — AI agents that reply, look up orders and resolve routine cases - During business hours, in order of arrival — Any time, as soon as the ticket comes in - In every conversation — On cases outside the rules, refunds above a threshold and complaints - The conversation history — Each reply with the source it checked and the rule it used - Per support rep or per license — Per resolved ticket - The field technician types up the report after the visit — Agents that transcribe audio and photos and build the report in the cooperative’s format - That night or the next day, when there is signal and time — Right after the visit, even with a weak signal - In everything, from notes to sending — The agronomist reviews and signs off on the recommendation - Paper notes and loose photos on a phone — A report with photos, location and who signed off - The technician’s hours — Per logged visit - A data analyst builds each dashboard on request — Agents that read the business context and build the dashboard from a plain-language request - In the request queue, over weeks — In one day, in the BI case we delivered - Throughout the build — An analyst checks the numbers and assumptions before publishing - The queries, kept by whoever wrote them — Assumptions, data sources and the approval for each dashboard - Analyst hours or a fixed-price project — Per dashboard delivered - People on the team — They set the rules, check what the agents prepared, decide the exceptions and are accountable for the result. - AI agents — They read the data, fill in systems, build reports and answer routine questions, always within what has been allowed. - The SaaS, ERP and data you already have — They keep holding the data, the rules and the history. Nothing needs to be replaced to get started. - Agribusiness and cooperatives — The field visit recorded and sent to the agronomist — They transcribe the audio and photos the field technician records in the field, even with a weak signal, and build the report in the cooperative’s format. — The agronomist reviews and signs off on the recommendation before it reaches the grower. — Per recorded visit or per grower served each month. - Financial services — The analysis dashboard, published and reviewed — They read the business context, query a protected data layer and build the dashboard with its assumptions and sources. — An analyst checks the numbers and assumptions before publishing to the business team. — Per dashboard delivered or by monthly subscription with an agreed volume. - Accounting and business owners — The monthly analysis, ready for the business owner — They cross-reference the company’s accounting and financial data and prepare indicators, alerts and scenarios. — The accountant reviews the analysis and talks with the business owner about the decisions. — By service subscription, per company served. - Customer service — The resolved ticket — They reply, look up orders and systems and resolve routine cases within the defined rules. — Exceptions, refunds above a threshold and complaints go to a person on the team. — Per resolved ticket, with a monthly minimum. - Public sector — The case file, checked and ready for a decision — They check documents, fill in the system and flag anything missing, following LGPD (Brazil’s data protection law). — The responsible public servant signs the final decision on each case. — Per completed case, under the contract with the agency. - Events — The checked-in attendee — They verify registrations and payments, issue the badge and answer attendees’ questions. — The organizers approve exceptions, complimentary passes and guest lists. — Per checked-in attendee or per event. - [Service as a Software](https://www.toglab.co/en/projeto-bi-investimentos.html.md) — Validated with a client — Agent-driven BI at an investment advisory firm — The business team requests the dashboard in plain language and receives it ready, reviewed by a person. Dashboards that used to take weeks now ship in a day. — View case study - [Service as a Software](https://www.toglab.co/en/contato.html.md) — Concept — BI and AI for business owners — With an accounting partner, small and midsize business owners get ready-made analyses and scenarios by subscription, without having to operate a BI tool. — Talk about this model - [Service as a Software](https://www.toglab.co/en/projeto-superagro.html.md) — Proposal stage — Intelligence hub for cooperatives — Modules for each business area, with reports and alerts delivered ready to use and licensing per cooperative, with no per-user cost. — See SuperAgro, which provides the foundation - [Software as a Service](https://www.toglab.co/en/projeto-superagro.html.md) — Tog Lab product — SuperAgro — Growers, agronomists and co-ops working on the same field data, in an app that works out in the field. — View case study - [Software as a Service](https://www.toglab.co/en/projeto-tog-events.html.md) — Tog Lab product — Tog Events — An event’s attendees, inventory and deliveries in one place, even offline. It started as a client project and became a platform. — View case study - [Innovation](https://www.toglab.co/en/insights-task-as-a-service.html.md) — Task as a Service: agents running tasks, with a person accountable for the result — What changes when a company buys the task done, how to choose the first one and where the person steps in. - [Innovation](https://www.toglab.co/en/insights-carro-sem-motorista.html.md) — Service as a Software, a layer on top of SaaS — The pricing models the market already uses and how to design a service delivered by agents and people. - [Innovation](https://www.toglab.co/en/insights-carro-sem-motorista.html.md) — The unit of value: how to charge for delivered work — How to find the deliverable the customer recognizes and turn it into a price.