Enterprise Software, AI & Consulting

Write down the requirements that genuinely differentiate your business. If an existing product covers the essentials, compare configuration and integration before commissioning custom software. Build when a material requirement cannot be met economically, and you can support the system beyond launch.

Compare total ownership cost: licences, integration, migration, training, security, support and exit costs. Check who owns the data and how you would export it. A cheaper first year can hide an expensive dependency.

Measure a repeatable task before automating it: volume, time per task, error rate and cost of correction. Subtract model usage, integration, human review and ongoing maintenance from the expected benefit. Hours saved are not cash savings unless that capacity can be used productively.

Test a bounded pilot on representative inputs. Include difficult cases, confidentiality checks and a human fallback. Expand only when the quality and economics hold up against the original baseline.

Map one important workflow with the people who use it. Identify handoffs, duplicated entry, delays and the systems involved. Review a representative sample of evidence rather than relying only on opinions or a vendor demonstration.

The output should be a prioritised set of options, dependencies, indicative costs and risks, plus a clear next decision. Sometimes the right answer is a process change, better training or a small integration, not a new platform.

Agree who owns the system, how incidents are reported, which changes need approval and how recovery is tested. Confirm access, documentation and handover before the delivery team leaves.

Track reliability, operating costs and the business measures agreed at the start. Review the causes of repeated support requests before adding features. Ongoing support and response commitments should be explicitly scoped, not assumed.