Case Study
A City of London management consultancy recovered 22 hours of billable staff time per week by automating proposal generation, client onboarding documents, and invoice processing with Softomate's AI automation stack.
City of London management consultancy
A City of London management consultancy recovered 22 hours of billable staff time per week by automating proposal generation, client onboarding documents, and invoice processing with Softomate's AI automation stack.
A boutique management consultancy based in the City of London had built a strong reputation over nine years delivering strategy work to mid-market businesses across financial services, professional services, and property. With a team of 14, including six senior consultants, the firm was growing steadily but had hit a capacity ceiling it could not break through by hiring alone.
The bottleneck was not client delivery. It was the administrative workload surrounding each engagement. Every new project generated a significant volume of repetitive documentation: a scoped proposal drawn from notes and previous templates, an onboarding pack including legal terms, data processing agreements, and NDAs personalised to each client, invoices generated from timesheet data, and progress reports formatted to the firm's house style. None of this required expert judgment, but all of it required time that the firm's most experienced people simply did not have.
Nobody had formally measured how long these tasks took until Softomate ran a time audit during the initial discovery phase. The results were striking. Senior consultants, billing at rates above £1,000 per day, were spending an average of 3.2 hours per week on proposal formatting. The office manager was spending 11 hours per week on invoice generation and onboarding document preparation. Across the firm, 22 hours of billable or near-billable time was disappearing into administrative work every single week.
The impact reached the business development pipeline as well. Because proposals were slow to produce, the firm had developed a habit of sending a holding acknowledgment and then taking three to four business days to follow up with the actual proposal. Several prospects had been lost during that gap, and the partners were well aware of it. Reducing the proposal cycle was not just an efficiency question; it was a business development imperative.
The principal partner summed up the situation clearly in the initial discovery session: the firm knew what needed to change, and it simply needed to stop doing the parts a machine should be doing. A brief earlier trial of a general automation tool had not progressed because the tool could not generate the context-specific, professionally formatted documents the consultancy's work required. What they needed was an automation that understood their process well enough to produce outputs a senior consultant would be comfortable putting in front of a client.
Softomate's approach began with detailed process mapping. Over two weeks, the team documented every step in the proposal, onboarding, and invoice workflows, identifying the inputs required, the decisions involved at each stage, and the degree of human judgment each step genuinely needed. The conclusion was that all three processes could be automated end-to-end for the majority of standard engagements, with human review retained for non-standard or high-risk cases where the context required consultant judgment.
The proposal automation used a retrieval-augmented generation system built on GPT-4o. The system ingested the firm's archive of previous proposals, extracting reusable templates, fee structures, scope language, and outcome statements categorised by service type. When a consultant completed a structured intake form, which took an average of four minutes, the system generated a complete first-draft proposal in the firm's house style, pre-populated with relevant case references and fee tables. Consultants moved from building proposals from scratch to reviewing and refining a solid first draft. Average proposal time fell from 2.8 hours to 35 minutes per engagement.
The onboarding document automation connected to the firm's CRM via API and used a document generation integration to produce personalised NDAs, engagement letters, and data processing agreements from approved legal templates. Client details, scope specifics, and billing terms flowed directly from the CRM into the documents, which were then dispatched via e-signature platform without any manual intervention from the office manager. The legal team reviewed and formally approved the template set once at the outset, providing sign-off for all future outputs generated from those templates.
The invoice automation pulled approved timesheet data from the firm's time-tracking platform via its REST API, calculated fees against each project's billing schedule, and generated invoices in their accounting platform with line-item descriptions matched to actual work delivered. A task that had taken the office manager 11 hours per week was reduced to 90 minutes of reviewing and approving a pre-built weekly batch.
Softomate ran three weeks of parallel testing before go-live, during which both the automated and manual workflows ran simultaneously and outputs were compared in detail. The firm approved automated outputs at a rate of 97% without modification. The remaining 3% led to targeted refinements to the template set before full deployment. The total build and integration work took eight weeks from the end of the scoping phase.
In the first full quarter after deployment, the firm saved a measured 22.4 hours of staff time per week. Senior consultants recovered an average of 3.1 hours each, the office manager recovered 8.5 hours, and the remaining savings came from junior team members who had been assisting with formatting and document collation tasks.
The financial impact was significant. At an average consultant day rate of £1,100, recovering 3.1 hours per week per consultant across six consultants represented a meaningful increase in available billing capacity. The firm won two additional client engagements within the first quarter that the partners attributed directly to faster proposal turnaround. Average proposal delivery time fell from four business days to same-day for standard engagements, a change that immediately distinguished the firm from larger, slower-moving competitors.
In at least three cases during the first quarter, prospects specifically mentioned the speed of the firm's proposal response as a reason for choosing them rather than a larger alternative. This was a direct reversal of a pattern the partners had observed before the automation was in place.
The office manager, who had been considering leaving due to workload pressure, described the change as transformative in a review session three months after deployment. She moved from reactive administration to proactive client relationship management, a role the firm had long wanted to create but had never had the capacity to resource properly.
The total cost of the engagement was recovered within seven months of go-live. The consultancy has since extended the automation to project reporting, where a pre-populated weekly progress report is generated from project management notes and handed to the relevant consultant for review and dispatch. Softomate continues to provide quarterly optimisation reviews and adds new automation modules as the firm's needs evolve.
The engagement has also changed how the firm approaches headcount planning. Rather than recruiting a second office manager to handle growing volume, the partners redirected that headcount budget into a new client success role, which the firm had long wanted but could not previously justify. The automation made that reallocation possible without any reduction in operational capacity or service quality.
Names withheld to preserve confidentiality.
Work with us
Every project we take on has a measurable outcome. Talk to our London team and we will show you exactly how we would approach your challenge.
Softomate Solutions Limited
Deen Dayal Yadav
Online