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Soft Pyramid

Managed AI agents

Agent as a Service: Managed AI Agents Built and Run for You

Agent as a Service means Soft Pyramid builds, hosts and runs AI agents for your business as a managed service. We design the agent around one job, put it into production, watch how it behaves and keep improving it, so your team gets the result without having to run the system.

Soft Pyramid is a software company led from Frisco, Texas, with a delivery center in Lahore, Pakistan. We have been in business since 2013.

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What is Agent as a Service?

Agent as a Service (AaaS) is a way to get an AI agent without having to run it yourself. The provider builds the agent for one of your workflows, hosts it, monitors it and keeps improving it as a managed service.

At Soft Pyramid, one team answers for the agent from the first build onward, so your staff use the result and do not have to maintain the system behind it.

Who it is for

This service suits teams that want the outcome of an AI agent and would rather not staff, host and watch one themselves.

  • Teams without in-house AI engineers

    You know which task should be easier, but you do not have people to build, deploy and look after an agent.

  • Operations and support leads

    You own a repeatable, text-heavy task such as inbox triage, document intake, ticket handling or reporting, and you want it handled reliably.

  • Businesses that want one owner after launch

    You want a single accountable team for the agent, so a problem has one place to go and nobody is left holding a system they did not build.

  • Companies with data rules to respect

    You need to agree what data an agent may see, which model provider it may use and where it runs, before anything goes live.

If you want to own the agent and run it inside your own engineering team, our agentic AI development service is usually the better starting point.

How it works

We take responsibility for the full life of the agent. Four parts of the service work together.

  1. Part 1

    Build

    We design and build the agent around one clearly defined job, connect it to the systems it needs with limited permissions and add human approval where an action matters.

  2. Part 2

    Host

    We deploy the agent and keep it running in an environment agreed during discovery, with credentials, backups and access handled as part of the service.

  3. Part 3

    Run and monitor

    We watch each run through logs and alerts, handle errors and keep the agent working as the tools and models around it change.

  4. Part 4

    Improve

    We review how the agent performs with your team, tune prompts, tools and rules, and extend it when there is a next job worth giving it.

Agent as a Service vs SaaS, chatbots and RPA

People often group Agent as a Service with other tools that automate work. These are the main differences in how each one is usually used.

  • Agent as a Service vs SaaS

    The other approach
    SaaS is ready-made software that you configure and use yourself. Every customer gets the same product.
    Agent as a Service
    An agent is built around one of your workflows and connected to your systems, and the provider hosts and runs it for you.

  • Agent as a Service vs chatbots

    The other approach
    A basic chatbot answers questions in a chat window, often from scripted flows or a fixed set of answers.
    Agent as a Service
    An agent can also use your tools and take approved actions, with a person approving the steps that matter.

  • Agent as a Service vs RPA

    The other approach
    RPA follows fixed, rule-based steps and works best when inputs are structured and predictable.
    Agent as a Service
    An agent can read unstructured input such as emails and documents and decide the next step within limits you set. The two can also work together.

Example agents

These are illustrative examples of agents that fit a managed service. They are not client results, and the right design depends on your systems, data and approval rules.

  • Inbound lead triage

    Reads each new enquiry, checks it against your CRM, drafts a reply and routes it to the right person for approval.

  • Support ticket assistant

    Searches your help content and past tickets, suggests an answer with sources and leaves the final reply to your support team.

  • Back-office document intake

    Extracts fields from invoices or forms, compares them with your records and flags mismatches for review.

  • Internal knowledge assistant

    Answers staff questions from approved documents and says so when it cannot find a reliable answer.

See how we build agents

How an engagement starts

  1. Discovery conversation

    You tell us the task, the systems involved and any data or hosting rules. A delivery lead says plainly whether an agent is a good fit.

  2. Written plan for the first agent

    We agree the job, the tools the agent may use, the approval points, the limits and where it will be hosted, in writing, before building.

  3. Build and test

    We build the agent and test it against real examples you approve, including awkward cases.

  4. Go live and run

    We release the agent, host it and monitor it with your team, with one lead answering for how it performs.

  5. Review and improve

    We review results with you on a regular rhythm and decide together what to tune, extend or stop.

Agent as a Service questions

What is Agent as a Service (AaaS)?
Agent as a Service is a managed way to use an AI agent. The provider builds the agent for a specific workflow, hosts it, monitors it and keeps improving it, so your team uses the result without running the system.
What does Soft Pyramid do in an Agent as a Service engagement?
We build the agent, host it in an environment agreed during discovery, monitor each run through logs and alerts, and review results with you to tune prompts, tools and rules. One delivery lead answers for how it performs.
How is Agent as a Service different from SaaS?
SaaS is ready-made software that every customer configures and uses themselves. With Agent as a Service, the agent is built around your own workflow and systems, and we host and run it for you.
How is it different from a chatbot or RPA?
A basic chatbot answers questions, and RPA follows fixed rules on structured inputs. An AI agent can read unstructured input, use your tools and take approved actions, with human approval where it matters. Agents and RPA can also work together.
Can an agent act without a person approving it?
That is a decision we make with you. By default we limit each agent to the tools and permissions it needs and require human approval before actions that change records, contact customers or spend money.
How do we get started?
Contact us with the task you want an agent to handle and the systems involved. A delivery lead will talk it through with you, say plainly whether an agent is a good fit and write down the plan for the first agent before any building starts.

Talk to us about running an AI agent for you

Tell us which task you want an agent to handle and which systems it needs to touch. A delivery lead will tell you plainly whether a managed agent is the right fit and what a sensible first agent looks like.

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