Client-specific AI, without vague promises.

Nucleus AI builds private, client-specific AI systems around five repeatable workflow categories: document and file Q&A; proposal, quote, and estimate drafting; customer inquiry triage and routing; internal knowledge and onboarding; and invoice, receipt, and form extraction. Each implementation is grounded in approved business material, defined review rules, and a documented architecture.

The default is the client’s own cloud tenancy, where the client controls its account and access and pays its cloud provider directly. A hosted path may be considered when a client lacks suitable cloud capability, but it is case-by-case and separately scoped. Exact models, data flows, external calls, and controls depend on the documented architecture and signed scope.

Frontier models are strong at broad, open-ended reasoning. A client-specific system grounded in approved source material can be better suited to repeatable, bounded work where terminology, templates, permissions, review rules, and traceability matter. Frontier services can still be used deliberately when the architecture and signed scope allow them; they are not treated as universally better or universally wrong.

The client retains ownership and control of its data and cloud account. Rights to configured models, integration work, configurations, support artifacts, and exit assistance are defined in the signed agreement. Nucleus AI retains its pre-existing workflow catalogue, reusable components, methods, and know-how. This website does not create or change those contract terms.

The typical fit is an operating business of roughly 10–250 people with established processes, real work volume, and no internal AI team. Examples may include construction and trades, professional services, healthcare practices, distribution, field service, and property management. Off-the-shelf tools may fit smaller or pre-revenue teams; organizations with an internal machine-learning team or enterprise-scale needs may be better served by a different partner.

AI-assisted output can be incomplete or incorrect. Human review is designed into material decisions and customer-facing work, with review steps, escalation paths, acceptance criteria, and known limitations documented for the scoped workflow. The system assists the work; accountable people decide what is used.

Engagements are scoped and priced individually. Cost is driven by the number of workflows, the systems they touch, the preparation required for approved material, and the review and governance design. Paid discovery produces a fixed build price attached to a written scope before build work is committed; the website does not publish a speculative range.

Discovery is a short paid engagement that produces a written scope, a fixed build price, and a schedule. The client keeps the scope, and the discovery fee is credited if the build proceeds. After the build, the operating service is offered month-to-month with 30 days’ notice; an annual option is available at a discount. The signed agreement defines the exact service responsibilities and exclusions.

It may be considered when a client lacks suitable cloud capability. Availability, infrastructure, access, security controls, data flows, commercial terms, and exit rights are evaluated for that engagement and documented in the signed scope and architecture. The website does not promise current hosted capacity or a universal hosting design.

That depends on the signed agreement and documented architecture. Rights to the configured system, documentation, access, transition work, and exit assistance must be agreed for the engagement. This website does not guarantee a particular transfer format, transition package, or level of assistance.

A conversational interface may be part of a workflow, but the offer is broader: defined business processes, approved source material, integrations, permissions, review rules, training, support, and refresh.

Timing depends on the selected workflows, material readiness, integrations, access, review requirements, and acceptance criteria. Discovery produces a schedule for the documented scope instead of relying on a universal implementation claim.

Requests outside the catalogue are evaluated separately. They are not silently added to a fixed-scope build.

Start with the AI project intake. It captures your goals, current process, systems, data requirements, and budget range, gives you a project brief PDF right away, and lets you send it to us for a reviewed build plan.