Why generic AI falls short for requirements management

and how vertical AI makes the difference — step by step, with and without Basewise.  

AI is broad, but Systems Engineering requires depth.  

Microsoft Copilot, internal knowledge agents, generative search engines — organizations are rolling out horizontal AI at scale. And rightly so: it helps employees find information faster, summarize texts, and answer standard questions.

But there is a second layer — one where “roughly right” simply isn’t good enough.  
In construction firms and consultancies working with UAV-GC contracts, EMVI procedures, and complex requirement specifications, Systems Engineering is about precision. Requirements must be verifiable, traceable, and aligned with contractual agreements. That’s not work for a generic assistant. It calls for AI that truly understands the process, the language, and the quality criteria of requirements management.  

Basewise is that vertical partner. Not “AI for everything”, but AI built specifically for the time‑consuming process steps in Systems Engineering.

Horizontal AI versus vertical AI  

Horizontal AI platforms are designed for breadth. They are generic, and work well when the user can judge the output based on general knowledge. “Almost right” is fine if you’re summarizing an email.  

Vertical AI is designed for depth. It is built on specific domain knowledge, process logic, and quality criteria. Basewise is familiar with INCOSE standards, the UAV-GC context, and the SE process steps that are central to infrastructure projects — not as a thin layer on top, but as the core of the system.  

These are not competitors. Horizontal AI supports the breadth of the organization. Basewise supports the depth: the specialist steps where errors directly affect scope, contract risk, and project outcomes.

Where it makes a concrete difference  

Requirement extraction from documents  
Reading, marking, and organizing a 300‑page requirement specification takes days — and the quality depends on who does it and how much time they have. The DRE scans documents systematically, identifies requirements, constraints, and implicit expectations, and returns a structured table. The SE professional becomes a reviewer, not a copyist.

Quality assessment of requirements  
A requirement like “the system must be robust” slips through most reviews unnoticed. The RQA assesses every requirement against eight INCOSE quality rules, provides a score, and suggests a concrete improvement. Reviews become faster, deeper, and more consistent — regardless of who performs them.

Verification planning  
In practice, verification is often scheduled “somewhere later in the project”, only to discover at handover which requirements have not been demonstrably verified. The REF links requirements to evidence in existing project documents and makes verifiability explicit before the design is finalized. No surprises at handover.

Traceability  
The origin of requirements too often lives in people’s heads or is scattered across email threads. When teams change, that knowledge is lost. Tracy records traceability from source requirement to derived requirement to verification evidence — so audits are feasible and contract disputes can be resolved based on facts.

The real cost of poor requirements management  

It may sound abstract, but the numbers are concrete:  
Rework in construction projects costs on average 5–12% of total project costs. 70–85% of those rework costs can be traced back to errors in or around the requirements. A defect found late in the lifecycle can cost up to 100× more to fix than if it had been discovered early.  

In UAV-GC contracts, the contractor bears the design risk. A requirement that is not verifiable, an expectation that has not been made explicit, a verification step that is planned too late — these are contractual risks, not just quality issues.  

Basewise addresses this early. Not by replacing the expertise of SE professionals, but by systematically supporting the steps that are time‑consuming and prone to error.

Start small, measure clearly  

Most organizations that start with Basewise begin with a single process step and one document flow. Choose an entry point — requirement extraction, quality analysis, or verification planning — apply it in a real project context, and measure time savings and quality improvements compared to the old way of working.  

From there, adoption grows organically.

Vertical AI is not a luxury — it is the logical next step.  

Horizontal AI delivers breadth. Basewise delivers depth — exactly where it is needed: in the process that has the greatest impact on scope control, contract risk, and project outcomes.  

Not “AI for everything”, but AI that understands Systems Engineering.