Why Engineering AI is different from a general AI chatbot

A general AI chatbot is trained on a broad slice of the internet. It can talk about engineering, but it answers engineering questions from memory, and memory is not the right place to store numeric reference data.

The failure mode

Ask a general chatbot for the section modulus of a W12x26 beam and you will get an answer. It may be correct. It may be wrong by a few percent. It may be wrong by 30 percent. You will not know unless you cross check it against the steel manual. At that point the chatbot has not saved you any work.

The same problem shows up for any table based value: allowable stresses, friction factors, thermal conductivities, standard wire sizes, motor full load currents, pipe dimensions. These are not things a language model should be trying to remember.

The difference here

When you ask EngDatabase AI for the section modulus of a W12x26, it opens the AISC shape table, pulls the row, and reports the value. There is no risk of a fabricated reference value because the answer comes from a table, not from training data.

The same principle applies to every kind of reference value. All of it lives in structured tables. None of it is answered from model memory.

Calculations, not estimates

Asking a general chatbot to “size a beam” is asking it to do math in its head. It may get the right answer for a simple case. It will get the wrong answer for a case that needs a lookup, an interpolation, or a code check.

EngDatabase AI runs the actual calculator, which in turn reads actual tables, which in turn follow actual code provisions. The number you receive is reproducible. You can verify it by opening the same calculator and entering the same inputs, and you will get the same result.

Same language ability, plus real data

EngDatabase AI is backed by a frontier language model, so it has the same reasoning and conversational ability you would expect from a top tier general chatbot. You can brainstorm design concepts with it, talk through trade offs, walk through a problem out loud, draft narrative text, or get a plain English explanation of a code provision. None of that is off limits.

The difference is what happens the moment the conversation hits a number. A general chatbot keeps talking from memory. EngDatabase AI reaches for the right reference table or calculator, pulls the real value or runs the real calculation, and brings it back into the conversation.

The result is a single tool you can use for both sides of engineering work: the open ended design discussion side and the grounded numerical side. You are not switching between a chatbot and a reference book.

Side by side

• Reference values: general chatbot answers from memory, may hallucinate; EngDatabase AI looks up the table.
• Unit conversions: general chatbot usually correct but can drop precision; EngDatabase AI uses a deterministic converter.
• Sizing calculations: general chatbot estimates; EngDatabase AI runs the calculator.
• Traceability: general chatbot rarely cites a source; EngDatabase AI names the table or calculator used.
• Reproducibility: general chatbot responses drift run to run; EngDatabase AI results are deterministic for the same inputs.

Try it

The AI assistant is available on the free plan. Open the AI page and try the same question you would ask a general chatbot. You will see the tool calls and the sources inline with the answer.