GPTProX can assist a software company in formulating an optimal bid proposal for a large project. The company’s knowledge base contains:
When the high-level functionality requirements for the bid are entered into GPTProX, its conversation with ChatGPT suggests an implementation approach and required developer resources.
The logic programming validator parses these suggestions to query the knowledge base. It verifies the feasibility per the company’s current staffing and constraints. Unvalidated suggestions are discarded.
The category theory module further vets the implementation plan by modeling it against the requirements to catch inconsistencies. This enhances the robustness of the final proposal.
For the actions of assembling a technical team and estimating costs, GPTProX’s optimization solver interfaces with the knowledge base. It generates an optimal allocation and schedule of developers based on skillsets, availability windows, and interdependencies.
These optimized outputs are combined to produce a comprehensive project execution plan. GPTProX runs financial calculations to attach detailed cost estimates to this plan.
The final output is an accurate bid proposal aligning staffing, timelines and budgets to the project’s technical and functional needs. The knowledge base integration makes this feasible bid generation automated, rapid, and reliable.