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About Us

Autonomous AI Agent Engineering Built For Enterprise Delivery

Aerosoft is an engineering partner for teams that need Autonomous AI Agent Engineering to operate inside real systems, not isolated demos. We build agent-driven automation and custom software that is designed for uptime, governance, and long-term ownership.

Why Aerosoft Exists

Most Enterprise Teams Do Not Have A “Lack Of AI.” They Have Bottlenecks

fragmented data, brittle workflows, manual approvals, and systems that were never designed for autonomous execution.
We built Aerosoft to deliver Autonomous AI Agent Engineering that reduces operational load without creating new risk. That means we approach every build as a system, not a feature. Inputs, permissions, failure modes, audit trails, cost controls, and clear ownership all exist from day one.

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(4.9)

Our Values

Enterprise AI Implementation Partner

Enterprise buyers do not need a vendor that “builds something cool.” You need an Enterprise AI Implementation Partner who can align stakeholders, define hard requirements, and ship into production without treating your environment like a lab.

Your data has rules

boundaries, and consequences

Your systems have constraints

and those constraints matter

Your teams need clarity on ownership

runbooks, & change management

Your security and compliance

posture cannot be an afterthought

Pragmatic AI

Generative AI Solutions For Business

Generative AI Solutions for Business only create value when they are connected to the decisions your company already makes. The work is not “add AI.” The work is to make existing workflows faster, more accurate, and more consistent under load.
Aerosoft builds Generative AI Solutions for Business around the practical questions that determine ROI:

How It Works

Legacy System AI Integration

Enterprise ROI is often locked behind older systems: ERPs, CRMs, ticketing platforms, internal databases, and workflow tools that were not designed to cooperate. Legacy System AI Integration is where many AI initiatives succeed or fail.

01

System Boundaries

Identify system boundaries and integration constraints early

02

Clear Mappings

Create clear mappings between legacy data and agent actions

03

Partial Adoption

Design for partial adoption, so teams can roll out safely

04

Integrations

Avoid “single point of failure” integrations that break operations

Our Features

Full-Stack AI Product Engineering

Teams often get stuck between prototypes and production because nobody owns the whole stack. Aerosoft delivers Full-Stack AI Product Engineering so your agents, integrations, and interfaces are built as one cohesive product.

Agent Orchestration

Agent orchestration and tool use aligned to business processes

Operator Interfaces

UI layers where operators review, approve, and intervene

Observability & Audit Trails

Logging, observability, & auditability for production operations

Deployment Architecture

Deployment patterns that match your environment and release discipline

Aerosoft Is Structured To Deliver Requirements That Hold Up Under Production Pressure.

Integration Depth Across Legacy

Modern stacks

Accountable delivery team

How We Work

When you engage Aerosoft for Autonomous AI Agent Engineering, you should expect:

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Ready To Evaluate Fit

If you are planning Autonomous AI Agent Engineering and need a partner who can ship into real systems, let’s have a technical strategy call. We will discuss scope, constraints, and what it will take to deliver safely in your environment.

Frequently Asked Questions

Let’s Make Something That Holds Up

If you want a second opinion on feasibility, risk, or integration approach, we can run a short technical discussion. You will leave with clearer scope and a realistic delivery path.

Autonomy is scoped. We define what actions the agent can take, what requires approval, and what must stop and escalate. The goal is controlled execution, not uncontrolled automation.

We design permission models around least privilege, with explicit tool access, audit logging, and clear separation between read and write operations. This is part of the baseline architecture, not a post-build patch.

Yes. Legacy System AI Integration is a core delivery capability. We focus on stable interfaces, reliable data mapping, and fallbacks so production workflows do not become fragile.

Most engagements start with a scoped build plan: workflow definition, system boundaries, success criteria, and a delivery roadmap. From there, we move into implementation with clear milestones and operational readiness for launch.

You do. We deliver documentation, runbooks, and maintainable architecture so your team can operate and extend the system. Where ongoing support is needed, it is defined explicitly, not implied.