Should you build your own AI for responding to tenders or buy a solution?

In brief.
To automate responses to tenders and questionnaires, a company has two options: develop its own AI tool in-house (build) or subscribe to a solution on the market (buy). Build is appealing: control, confidentiality, an innovation budget. Its real economics are unfavourable: market analyses put a serious project at between $1.4 million and $2.2 million over three years, against $120,000 to $360,000 for a solution, with 6 to 12 months before the first value. The decision framework: build what makes you unique, buy what makes you efficient.

Data control does not require building

It is the most legitimate reason to build, but it calls for something else: requiring from a vendor what build 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 the internal project

The prototype that works within a few days represents about 10% of the total effort; the remaining 90% is putting it into production: access rights, connectors, scaling, security, support, model maintenance, and above all continuous evaluation of reliability. Add to that the opportunity cost: tying up 4 to 8 scarce engineers on an internal support tool, while the time to value drifts to 6 to 12 months.

Longevity, the blind spot

AI models evolve at a quarterly pace: an architecture built around the model of the moment ages quickly, and it is the vendor, not your IT department, that should absorb this renewal. The same logic applies to regulation: who updates the internal rules when the texts change? There remains the case where building is justified: when the document process is the differentiator you sell to your customers. For everyone else, one question for 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 build (a private AI per customer, on-premise or sovereign cloud, data deleted at the end of the contract) with the industrial strength of a vendor (reliability measurement, security, regulatory watch, contractual commitments).

When is in-house development justified?
When document processing is the product your customers buy, not a support function.

Does build guarantee better confidentiality?
No: a private deployment with a sovereign vendor offers the same isolation, without the investment.