AI Automation &
Custom AI Solutions

We build custom AI chatbots, workflow automations, request and document classification, predictive analytics and computer vision solutions. We integrate them with the tools you already use, such as your CRM, email and website. The goal is not an impressive demo but a process your team uses every day, running noticeably faster.

It depends on data preparation, the number of integrations and the risk level of the process. A narrowly scoped pilot can be validated faster; solutions that work across several systems and take critical actions need longer discovery, testing and security work. At the end of discovery we give you a clear roadmap and timeline.

Cost depends on process complexity, data quality, integrations and usage volume. The one-off development fee should be planned separately from usage-based monthly costs such as model/API usage and hosting. We recommend starting with a measurable pilot and scaling based on results, and we define the scope in a free consultation.

The best candidates are repetitive, high-volume processes with outputs you can check: classifying incoming requests, extracting data from documents, drafting quotes, answering frequent customer questions and reporting. Fixed-rule tasks are often more reliable with traditional automation, and for high-risk decisions we design human approval into the system.

We design for privacy from day one: we process only the data needed, limit access rights, separate environments and explain clearly which provider receives which data under what terms. Whether data may be used for model training depends on the chosen provider and settings, and we settle this before the project starts. The final setup must meet your data protection obligations.

Yes. We integrate AI solutions with your existing systems and workflows via APIs. First we map where data comes from, where it goes and which steps need human approval; then we test with real data before going live. After launch we keep monitoring performance and improving both the model and the workflow.

In most projects, yes: a model that works well needs clean data that represents the process. Sample requests, documents, product information or historical records can be used for this. If your data is scattered, we help with collection, cleaning and knowledge-base preparation; this work is scoped separately.