Put AI to work across your business.

Helps a business decide where AI belongs, design the workflow, choose an approach and deliver the work to make it usable, including data and system readiness, integration, testing, staff adoption and measurement, not just recommending software.

Not necessarily. We start with what you already use and assess whether it can support the process. An integration or configuration change may be enough. Replacement should have a clear business reason.

No. Traditional automation follows defined rules. AI can help with language, documents or information that doesn’t arrive in a consistent format. Many useful workflows combine both, with human review where needed.

Potentially, depending on the software, available integrations, permissions and the type of information involved. We assess compatibility and data handling before proposing an approach.

It depends on the workflow, data readiness, integration complexity, security requirements, testing and support. A useful first step is to define one problem and estimate both the effort and the likely value. Lime scopes paid discovery and implementation separately before work begins.

There is no responsible universal timeline. A bounded workflow using existing tools differs considerably from a custom integration involving sensitive information and several departments. Timing is set after discovery and scope approval.

We assess what information is involved, whether it should be used at all, who needs access and which controls are required. Regulated or particularly sensitive data needs client-side privacy, security and legal review. We don’t treat a consumer AI account as an approved destination for confidential information.

Then we should say so. Better forms, cleaner data, a clearer process or conventional automation may deliver more value with less cost and risk.

Yes. In many workflows, that is the correct design. AI can prepare, organize or summarize information while a designated person approves customer-facing responses, commercial commitments and consequential decisions.

We define a baseline and success measures before implementation. Depending on the process, these may include time per task, corrections, speed of handoff, user adoption, exception rates or qualified business outcomes. We do not promise savings before they can be measured.

We can help with preliminary fit, technical scope, milestones and application information. You and your accountant provide and verify financial documents, and your business submits the application. Detailed support is a paid engagement. Funding decisions belong to the program administrator.

Start with a recurring task that has usable information, an accountable owner, manageable consequences if it goes wrong and a result you can measure. The first step may be improving an existing tool or connecting systems. Custom development becomes relevant when the requirements justify it.

Ownership and usage rights should be stated in the agreement before work begins. Ask about project-specific code, existing components, source access, accounts, documentation, data export and handover. External AI models, third-party software and reusable components may be licensed separately. Funded projects also need to satisfy the program’s IP requirements. Lime’s proposal should make these terms explicit.

There may be continuing charges for hosting, software licences, AI usage, backups and maintenance. These should be shown separately from the build fee, with assumptions and spending controls. Owning project-specific code does not remove third-party operating costs.

The proposal should explain support requirements, service coverage, access and handover options. Discuss who will maintain the tool if your team or another provider takes over. Agree on the operating arrangement before the build, including documentation, account access and any transition work.

Involve the people doing the work, name a process owner and reserve time for a small pilot. Training should cover normal tasks, mistakes, human approvals, permitted information and how to get help. Use realistic practice, short instructions or recordings, and verify that staff can complete the task. Any refresher support should be included in the agreed scope.

Start with one process and a small user group. Test alongside the current method, keep a fallback and agree on success criteria before changing how work is done. Expand when the workflow is reliable enough for the task and users are ready.

Inconsistent information, unclear ownership, limited integration access, staff without time to test and a scope that keeps growing can all delay progress. Identify these early, alongside permissions, operating costs and the consequences of incorrect outputs.

Potential benefits include less re-entry, faster processing, fewer missing details, easier access to information and more consistent follow-up. Set a baseline and measure the actual outcome. Time freed up is capacity. It becomes a cash saving only when it reduces a real expense; any additional revenue needs its own evidence.