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In brief.
To automate responses to tenders and questionnaires, a company has two routes: build its own AI tool in-house, or subscribe to a market solution. Building is appealing: control, confidentiality, an innovation budget. Its real economics are unfavourable: market analyses put a serious project at between USD 1.4 million and 2.2 million over three years, against USD 120,000 to 360,000 for a solution, with six to twelve months before the first value is delivered. The decision framework: build what makes you unique, buy what makes you efficient.
Controlling your data does not require building
This is the most legitimate motivation for building, but it calls for something else: demanding from a vendor what building promised — a private deployment, on your premises or on a sovereign cloud, with no pooling and guaranteed deletion at the end of the contract. Control without the construction project.
The real economics of an internal project
The prototype that works within a few days represents roughly 10% of the total effort; the remaining 90% is production readiness: access rights, connectors, scaling, security, support, model maintenance and, above all, continuous reliability evaluation. Add the opportunity cost: tying up four to eight scarce engineers on an internal support tool, while time to value drifts from six to twelve months.
Longevity, the blind spot
AI models evolve on a quarterly rhythm: an architecture built around the model of the moment ages fast, and it is the vendor, not your IT department, that has to absorb that renewal. The same logic applies to regulation: who updates the internal rules when the legislation moves? One case remains where building is justified: when the document process is your differentiator, sold to the client. For everyone else, one question at the investment committee: “how does this internal tool improve the product we sell?”.
The Optivalue.ai approach
Optivalue.ai was designed to make the dilemma obsolete: the control promised by building (private AI per client, on-premise or sovereign cloud, data deleted at end of contract) with a vendor’s industrialisation (reliability measurement, security, regulatory monitoring, contractual commitments).
When is in-house development justified?
When document processing is the product your clients buy, not a support function.
Does building guarantee better confidentiality?
No: a private deployment with a sovereign vendor offers the same isolation, without the investment.
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