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Automation agencies need to identify, prioritise, and validate opportunities rapidly. Auditic is built for exactly this workflow.
Clients have hundreds of processes. Finding the right automation candidates requires systematic evaluation.
Automation projects live or die on business case approval. Credible ROI projections are essential.
Not everything that should be automated can be. Technical constraints must be identified early.
Balancing rapid ROI demonstrations with long-term transformation is a constant tension.
Automation concepts are new to many clients. Discovery must educate while evaluating.
IT departments increasingly build automation internally. Agencies must demonstrate superior value.
Automation discovery follows a distinct pattern: identify processes, assess automation potential, prioritise by value, and validate feasibility. Auditic structures each phase.
Process interviews capture volume, frequency, complexity, and exception rates. AI analysis scores automation potential using proven criteria. The opportunity matrix shows impact versus effort at a glance.
ROI calculations use automation-specific benchmarks: typical implementation time, expected accuracy improvements, and maintenance requirements. Clients see credible projections, not guesses.
Systematic process identification
Automation potential scoring
Impact vs effort prioritisation
Benchmark-backed ROI projections
Technical feasibility assessment
Client-ready business cases
Auditic is built for automation agencies and RPA boutiques that sell process automation, AI workflow and intelligent automation engagements. Whether your delivery stack is UiPath, Make, n8n, Zapier, Power Automate or a bespoke Python pipeline, the commercial workflow is the same: qualify a prospect, find the candidate processes, build a credible business case, and ship a proposal the buyer can actually approve. Auditic is the layer that sits in front of delivery and shortens every step of that motion.
Most agencies lose more revenue in the pre-sales gap than in delivery. Discovery calls produce free-form notes that nobody re-reads. Process candidates get described in conversation but never scored against a consistent framework, so prioritisation drifts toward whichever stakeholder shouts loudest. ROI estimates rely on round numbers and confidence rather than benchmarks, which is exactly why finance teams send proposals back for "more detail". Proposals then take a senior consultant a full day to assemble from scattered documents, and by the time the deck lands the buyer's enthusiasm has cooled.
Auditic compresses all of this. Discovery interviews and process walkthroughs are captured against a structured template, with pain points, current-state metrics and candidate processes extracted automatically from the transcript. Every candidate is scored against the same Impact, Effort, Urgency and Readiness model, so the prioritisation conversation is grounded in evidence rather than opinion. ROI is modelled with industry benchmarks for time savings, error reduction and throughput, and every figure shows its source. The proposal generator then assembles a buyer-ready document with the scope, the roadmap, the ROI model and the supporting evidence already in place.
A typical agency engagement runs in four steps. Qualify the prospect on a 30-minute call captured in Auditic, with the qualification rubric tagging fit, urgency and budget automatically. Run one or two process discovery sessions; candidate processes appear in the opportunity matrix with first-pass scores you can refine in minutes. Build the business case in the ROI workspace, choosing benchmarks for any input you cannot measure directly. Generate the proposal, attach the supporting evidence and send. Sales cycles shrink, win rates rise on better-anchored numbers, and the delivery team starts each project from a structured artefact instead of a fresh discovery brief.
See how Auditic transforms discovery in your industry.