The average lifespan of a technology product is three years. Not the company — the product. Most consumer applications, SaaS platforms, and enterprise software tools either undergo such significant changes within three years that they are effectively different products, or they are discontinued.
Three years is not long enough to matter in agriculture. It is not long enough to matter in defence. It is not long enough to matter in medicine.
The systems that govern these domains operate on decade-scale time horizons. A farmer building soil health over twenty years cannot afford to have the diagnostic tool they depend on become unsupported in year four. A forensic agency building evidentiary case history around a particular imaging platform cannot have that platform discontinued or fundamentally changed mid-investigation. A hospital that has trained its staff on a clinical education system cannot rebuild that institutional knowledge from scratch every time a vendor changes its product.
This creates a specific obligation for anyone building technology in these domains. Not the obligation to be innovative — that is easy. The obligation to endure.
What Endurance Requires
A system that is genuinely designed to endure is different in its architecture, its business model, and its organisational philosophy from a system designed for growth and exit.
Architecturally, enduring systems are built with a conservatism about dependencies that fast-moving product teams rarely exercise. Every external dependency — a third-party API, a cloud service, a database provider — is a potential point of failure in ten years. Systems designed for longevity either own their core infrastructure or are designed to be portable across infrastructure providers with minimal friction. They use open standards where open standards exist. They document their internal workings in ways that allow a different team to understand and maintain the system if the original team is no longer available.
In their business model, enduring systems are designed so that the incentives of the builder align with the long-term interests of the user. A system whose revenue depends on users continuously upgrading to new versions has an incentive to make old versions less functional. A system whose revenue comes from genuinely useful ongoing service has an incentive to keep the system working well. The alignment between commercial incentive and user interest is a feature of the business model, not a moral position.
Philosophically, organisations that build enduring systems have made a decision about what they optimise for. They optimise for reliability over novelty, for correctness over speed, for trust accumulated over years rather than attention accumulated over days. These are not natural alignments for a technology company in an industry that rewards growth metrics and exit valuations. They require deliberate choices about what kind of institution to be.
The Failure Mode of Short-Cycle Technology
The failure mode of systems that are not designed to endure is visible throughout the technology landscape in India's critical sectors.
Digital agriculture platforms have launched, attracted farmers to their systems, accumulated data about farming practices and market conditions, and then shut down or pivoted when funding conditions changed. The farmers who had adopted these platforms were not just inconvenient — they were sometimes in a worse position than if they had never adopted the platform, because they had made decisions based on data and advice that was no longer available, and the institutional knowledge they had built around the tool was now useless.
Electronic health record systems in district hospitals have been implemented, under-supported, and eventually abandoned — leaving clinicians with hybrid paper and digital workflows that are worse than either would be alone.
Agricultural input platforms have changed their terms of service, their pricing structures, and their product offerings in ways that made business sense for the company but created operational disruption for the farmers who depended on them.
These failures are not failures of bad actors. They are the predictable outcome of building technology for contexts that require decade-scale commitment with business models and organisational cultures optimised for eighteen-month cycles.
The Truffaire Commitment
When we deploy ARCORA with a farmer producer organisation, we are not deploying a product. We are establishing a relationship with a time horizon that extends well beyond the current growing season.
The data that accumulates through ARCORA — the disease records, the treatment outcomes, the seasonal patterns, the crop-specific knowledge — is not data that we extract for our commercial benefit. It is institutional knowledge that belongs to the FPO and its member farmers. Our obligation is to make that knowledge more accessible and useful over time, not to own it.
When we build CIPHER for law enforcement applications, we are building for evidentiary use cases that require the technology to be consistent, documented, and demonstrably reliable over the years it takes for cases to move through the judicial system. The imaging system used to document a crime scene in 2025 may need to produce consistent, comparable results from the same equipment in 2030.
This is not a constraint we resent. It is the core of what makes the work meaningful. Building systems that matter means building systems that last. And building systems that last means accepting the disciplines, constraints, and commitments that the technology industry has largely decided are incompatible with fast growth.
We have decided they are not. The two things can coexist. The decision to prioritise permanence is not a decision to grow slowly — it is a decision to grow in a direction that produces something worth keeping.