Dot Network designs and builds AI systems, automation and custom software for businesses that have outgrown manual operations and disconnected tools.

We work with startups, growing companies, service businesses, ecommerce operators and enterprise teams across different markets.

No. Dot Network is an engineering company focused on operational AI systems, automation and software products rather than traditional campaign or creative agency services.

We start with the operating problem, map the process and engineer a maintainable system around it. The output is working software and automation designed to become part of the business infrastructure.

Start with one process that is repetitive, slow, error-prone or dependent on manual handoffs. We can assess whether it needs automation, AI or custom software.

No. We use AI only where it adds practical value. Many systems are better solved with conventional software, integrations, workflow automation or a combination of these.

Yes. We generally integrate with the tools and data you already use before recommending replacement. The goal is a connected operating system, not unnecessary rebuilding.

Yes. Support can include monitoring, maintenance, improvements, integrations and further development after launch, depending on the system and engagement.

Timelines depend on scope and integration complexity. Smaller automation projects can move quickly, while larger operational platforms are delivered in staged releases.

Access to the people who understand the process, examples of the current workflow, relevant systems or data, and clear ownership for decisions and approvals.

Projects begin with discovery. We map the current process, identify constraints and exceptions, define the smallest useful system and agree the delivery stages before engineering begins.

Pricing is based on scope, complexity, integrations, delivery stages and ongoing operational requirements. We define the commercial structure after the system has been scoped.

Not as a fixed rate card. Two systems that look similar can have very different data, security, integration and operational requirements, so we price against the defined scope.

Project ownership, code, data and any third-party components are defined clearly in the engagement terms. Client-owned systems are structured so the business is not unnecessarily locked into Dot Network.

Accuracy depends on the task, data and model. We design around measurable performance, validation, observability and human review where errors carry meaningful consequences.

That depends on the selected providers and deployment architecture. Data handling and model-provider terms are reviewed as part of system design so the appropriate controls can be selected.

Production systems should expect exceptions. We design validation, logging, fallback paths and human checkpoints so mistakes can be detected, contained and corrected.

The goal is to remove repetitive operational work and improve capacity. The effect on roles depends on the process and how the business chooses to redesign work around the system.