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Readiness audit, use case prioritization by ROI, production deployment. AI that pays for itself inside 90 days — or we tell you not to build it.
Most mid-market AI projects fail for a predictable reason: they solve impressive problems instead of important ones. A chatbot on the website, a demo that wows the board, a pilot that never touches the P&L. Twelve months later the line item is real and the return is not.
The opposite failure is just as expensive: doing nothing while competitors compress their cost-to-serve and response times with tools that already work. The mid-market is exactly where AI advantage compounds fastest — large enough to have repetitive, expensive processes; small enough to deploy without an enterprise procurement cycle.
The problem is not access to AI. Every vendor will sell you some. The problem is knowing which three of the fifty possible use cases will return their cost within a quarter, and which forty-seven are theater.
We start with a readiness audit: data quality, process documentation, tooling, and team capability. AI deployed on top of undocumented processes and dirty data automates chaos. The audit tells you what is deployable now, what needs groundwork, and what to skip.
Then we prioritize use cases by expected ROI, not novelty. Every candidate is scored on cost saved or revenue created, implementation effort, data readiness, and operational risk. The output is a ranked roadmap where the top items are boring and profitable: document processing, customer response drafting, reporting automation, quality control, lead qualification.
Then we build and ship the top use cases to production — not pilots — with baseline metrics set before launch so ROI is measured against numbers, not impressions. This is not theoretical for us: Carlos runs AI products in production daily in his own companies, across multimodal assessment, voice, and LLM pipelines. The recommendations come from a builder, not from a slide.
From $40K
The readiness audit and use case prioritization run weeks 1–4. Deployment of the first use cases runs weeks 4–12. Measurement and iteration run through day 90, at which point every deployment has an ROI number next to it.
Pricing starts at $40K for audit, prioritization, and first deployment. The filter we apply is simple: if a use case cannot credibly return its cost within two quarters, we recommend against building it — including ours.
The boring ones. Document and invoice processing, first-draft customer responses, sales call summarization and CRM hygiene, report generation, lead qualification and routing, and quality control on repetitive outputs. These return their cost quickly because they attack hours that are measurable and expensive. Customer-facing novelty projects rank near the bottom of almost every ROI analysis we run.
No. Most high-ROI mid-market deployments run on current LLM platforms plus your existing systems, and need an owner, not a data science department. The readiness audit tells you honestly whether your data and processes support deployment now — and if they need groundwork, that becomes step one instead of a surprise in month three.
Baselines before launch, actuals at 30, 60, and 90 days. For cost use cases: hours saved times loaded cost, error rate reduction, cycle time. For revenue use cases: response time, conversion rate, pipeline throughput. Every deployment gets a target before it gets built. If we cannot define the metric, we do not build the use case.
No. Tooling recommendations are vendor-neutral and made per use case on capability, cost, and data handling. We build with the major model providers and standard automation tooling, and we document everything so you are never locked into us or them.
Your team owns the systems. Deployment includes documentation, training, and a named internal owner per use case. Some clients keep a quarterly review cadence with us to prioritize the next tranche of use cases; others run independently. Dependence on the consultant is a design failure.
Every engagement begins the same way: a 360-degree diagnostic that tells you what is actually constraining the business. Applications reviewed within 48 business hours.