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Tecyfy

AI deployment interview question · medium

How do you estimate the cost and latency of an AI solution for a customer before they commit?

The short answerBuild the estimate from measurements, not guesses: run the prototype on a representative sample of their real inputs, record tokens, model calls and latency per task, then multiply by their volumes with current prices.

The full answer

Build the estimate from measurements, not guesses: run the prototype on a representative sample of their real inputs, record tokens, model calls and latency per task, then multiply by their volumes with current prices. Present a range (typical and heavy cases), show the levers that move it (caching, smaller models, batching), and compare the total with the value of the work it replaces.

1. Measure per task

On 50 to 100 real examples, record for each task:

  • number of model calls (an agent may make 5 to 30),
  • input, output and cached tokens per call,
  • other costs: embeddings, reranking, search, tools,
  • time to first token, total time, and the slowest 5%.

2. Multiply out

Monthly cost = tasks per month × average cost per task, plus fixed costs (vector database, hosting, monitoring). Do it for a typical month and a peak month. For example: 40,000 tickets a month, 3 model calls each, about 9,000 input and 500 output tokens per ticket, at the chosen model's current prices, plus retrieval costs. Use the provider's current price list; Tecyfy's cost calculator at /prices/cost-calculator does this sum with current prices.

3. Show the levers

LeverEffect
Prompt caching of shared instructions and documentsCache reads cost 0.1 times the input price on most Anthropic models
Batching work that can wait (nightly classification)Half price on Anthropic's batch API
A smaller model for routing and extractionOften a fraction of the cost per call
Shorter outputs, fewer retrieved chunksFewer tokens per call
Fewer turns in agentsEach turn resends the conversation

4. Latency

Report time to first token (what users feel, with streaming) and total time, as typical and slowest 5%. Name what dominates: retrieval, tool calls or generation. If a target matters ("reply in under 3 seconds"), design for it now, because it may decide the model choice.

5. Compare with value

Cost per task against the cost of the current process: an agent's time per ticket × hourly cost, error costs, delays. A solution at 4 cents per ticket that saves 3 minutes of agent time is an easy decision; at 2 euros per ticket it may not be.

6. State the assumptions

Volumes, average input size, share of complex cases, prices on the date of the estimate. Prices change often, mostly downwards, so promise to re-check before contract renewal.

What interviewers look for: an estimate the customer can check and re-run themselves, and an honest range rather than one optimistic number.

Last updated 16 October 2026

Sources

Where each fact comes from

  1. 1Prompt caching
  2. 2Batch processing
  3. 3Reducing latency