Services
Provolve designs and builds AI-enabled tools that support people, processes, documents, decisions, and internal workflows.
The right approach to AI
AI is most useful when it is connected to real business processes. Provolve focuses on practical, controlled AI systems that improve internal workflows rather than isolated experiments that never reach production.
Automatically route, classify, and extract data from incoming documents - orders, invoices, compliance records, and reports.
AI-assisted checking of documents, contracts, and processes against regulatory requirements, with human sign-off built in.
Internal or external assistants that surface the right answers from your own data - not a generic chatbot.
Search and summarise internal documentation, policies, and operational knowledge for your team.
Automate recurring reports - operational summaries, financial narratives, status updates - reducing manual drafting time.
AI flags and recommends; people approve and override. Keeps humans in control while reducing cognitive load.
Technical approach
AI systems need to be reliable, auditable, and integrated with the rest of the business. Provolve builds with auditability and review steps built in from the start.
Discuss your AI projectCommon questions
Connecting a language model to a real business process so that work previously done by hand happens automatically, with anything needing judgement routed to a person. The value is not the model itself, it is the integration into the systems, data, and rules you already run.
High volume, document heavy, rule based work that is currently manual and where an occasional error is recoverable. Document intake, classification, supplier and customer correspondence, compliance checks, and report generation usually come top. Week one of a deployment produces a shortlist ranked by value, risk, and effort.
Constrained outputs rather than free text, retrieval from your own data rather than model memory, evaluation suites that measure accuracy against your real cases, human review wherever being wrong is expensive, and an audit trail of what the system decided and on what basis.
No. Data that is messy, duplicated, or spread across systems is the normal starting point. Dealing with it is part of the work rather than a prerequisite you have to fund and finish separately before anything useful can be built.
The first working system is typically live for real users between weeks two and four, following a first week spent on site mapping the workflow and auditing the data and systems it depends on. See how a deployment works.
Book a short call to talk through where the work is getting stuck, what your systems are costing you, and whether a deployment is the right answer. If it is not, you will be told that.