The problem
Every new customer required a professional services consultant to manually review their requirements, interpret them against product logic, and configure the system accordingly. This process took up to two weeks per customer and was a significant constraint on implementation capacity. Errors were caught late, creating rework cycles and delaying go-live.
The solution
We designed and built an AI-powered configuration bot that ingests a customer's requirements from a structured document or form, validates them against business rules, and generates the correct configuration output automatically. The system uses the Claude API for interpretation and n8n for orchestration, working within the client's existing infrastructure.
Results
75%
Reduction in consultant effort per configuration
2 wks → 2.5 days
Configuration time per customer
Zero
Configuration errors in production
3×
Implementations handled per week at same headcount
Commercial impact
The freed consultant capacity was redirected to higher-value implementation work and pipeline growth, rather than requiring additional headcount. The consistency of automated output also eliminated late-stage rework, reducing the hidden cost of configuration errors that had previously been absorbed by the professional services team.
Attribution
Enterprise SaaS provider, UK. Case study anonymised. Contact us to discuss applicability to your business.
The problem
Each new hotel required manual mapping of their booking channels : a painstaking, error-prone process that involved interpreting spreadsheet data, matching channel identifiers, and entering configuration manually. The same work was repeated for every hotel implementation, consuming significant consultant time. A single person carrying this knowledge also represented a delivery risk.
The solution
We built an automated channel mapping engine that reads raw channel data, applies intelligent matching logic using the Claude API, and generates validated configuration output ready for import. The solution eliminated manual interpretation, standardised the output format, and removed the single-point-of-failure dependency on one specialist.
Results
83%
Efficiency gain on channel mapping process
3 days → same day
Turnaround time improvement
30 min → 5 min
Per-hotel mapping time
"This will have a big cost saving and the speed to get these mapped is a big win for the business."
Implementation Lead, Hospitality Technology Provider (anonymised)
Commercial impact
1,625 hours per year returned to the professional services team. The automation also eliminated the delivery risk of depending on a single specialist, enabling the same throughput to be achieved by any trained team member using the tool.
Attribution
Hospitality technology provider, UK. Stakeholder quote verified. Case study anonymised.
The problem
Onboarding new hotel clients required consultants to review detailed property setup documents, check them against configuration requirements, and manually enter the validated data into the system. This was a highly repetitive, low-value task that consumed hours of senior consultant time per implementation and created a next-day turnaround on validation, slowing the overall onboarding timeline.
The solution
We built an automated configuration bot that reads the hotel's setup document, applies validation logic against the system's configuration rules, and generates the configuration output. What previously required a consultant to review, interpret, and re-enter is now processed automatically, with the consultant reviewing and approving the output rather than producing it.
Results
66%
Reduction in consultant effort per onboarding
Zero
Configuration errors in production
Next day → instant
Validation turnaround
Attribution
Property management software provider, UK. Case study anonymised.
The problem
When new venue clients switched from legacy or competitor systems, their historical data needed to be extracted, cleaned, reformatted, and imported into the new platform. Each migration was different: different column structures, different format conventions, different data quality. Consultants were spending between 45 minutes and an hour on each venue, and the volume of migrations in an average month made this a significant operational constraint.
The solution
We built an intelligent transformation pipeline that ingests raw data from any source format, uses AI to interpret column mappings and apply normalisation rules, and outputs validated data ready for import. The solution handles format variation automatically and flags exceptions for human review rather than failing silently.
Results
70–100 hrs
Saved per month on average
50+
Production migration runs completed
1 hr → seconds
Per-venue migration time
"This is a brilliant data automation that will shave 70–100 hours off onboarding effort in an average month."
Head of Operations, Hospitality Technology Provider (anonymised)
Attribution
Hospitality technology provider, UK. Stakeholder quote verified. Case study anonymised.
The programme
Rather than a single large automation, this engagement involved identifying five distinct manual workflows across a division, prioritising them by effort saved and implementation risk, and deploying automated solutions sequentially. This portfolio approach allowed early wins to build internal confidence while the larger automations were being designed.
Results
3,323 hrs
Capacity freed annually across 5 automations
87%
Efficiency gain on primary process
83%
Efficiency gain on secondary process
Eliminated
Offshore dependency for data processing
Strategic impact
The elimination of an offshore dependency reduced operational risk and repatriated control of a critical workflow to the UK-based team. The portfolio framing (treating this as a programme rather than a series of disconnected projects) also produced a governance model that the client is now using to evaluate and prioritise further automation opportunities.
Attribution
Enterprise SaaS provider, UK. Case study anonymised.