Language services

Is this post-editing or a rewrite? Quote the work before you accept the discount.

A fluent AI draft can hide hours of verification. Use a controlled pilot to choose post-editing or retranslation, expose hidden costs, and protect the quote from scope changes.

On this page
  1. The client asks for a discount before anyone has inspected the draft
  2. Define the output quality before measuring speed
  3. Compare post-editing and retranslation without making the test misleading
  4. Show the cost of each route, including the hidden work
  5. A small edit can require a large amount of checking
  6. Give account managers a repeatable intake checklist
  7. Questions we hear

The short version

  • An AI-generated draft does not establish a productivity saving. Test the actual material against the required quality.
  • Compare total effort for post-editing and retranslation, including research, review, file handling and reporting.
  • Use edit distance as one diagnostic. It does not directly measure reading, uncertainty or time.
  • Attach the quote to a defined input version and include a checkpoint when the content differs from the sample.

The client asks for a discount before anyone has inspected the draft

The enquiry sounds simple: the translation is already done, so your team only needs to check it. The draft reads smoothly. Then a linguist compares it with the source and finds inconsistent terms, missing qualifiers and passages that need rewriting. The deadline and discount have already been agreed.

Now the PM must choose between absorbing the extra effort, renegotiating during production or asking the linguist to work faster. None of those decisions can repair an estimate based on the assumption that machine output is always cheap to finish.

In a discussion about accepting AI post-editing assignments, translators describe sharply different conditions under which the work makes sense. Another post about client price pressure describes demonstrating the required work on sample pages. These accounts motivate a practical intake test, not a universal rule against post-editing.

The question for your LSP is whether this particular workflow reaches this client's acceptance criteria more efficiently than a fresh translation. Establish that before treating a draft as a saving.

Define the output quality before measuring speed

Ask what the content must do, who will read it and how the client will approve it. A support article, a brand campaign and a safety instruction can require different expertise and review. Agree the reference terminology, style expectations, context and final deliverable.

Avoid using light and full post-editing as self-explanatory labels. Write down which defects must be corrected and whether independent revision, layout checks, terminology research and explanatory feedback belong in the quote. The same label can hide different expectations.

A quote that starts with the actual work
  1. Inspect the inputs

    Check source, draft, language pair, context, file format and permitted use.

  2. Agree acceptance

    Define the required output and who decides whether it meets the brief.

  3. Compare methods

    Time representative post-editing and retranslation samples fairly.

  4. Quote the chosen route

    Include production, review, administration and a scope-change checkpoint.

Confirm the provenance of translation-memory matches too. A high match score describes similarity to stored material; it does not independently prove that the stored target was reviewed or remains appropriate for this context. Ask what evidence supports any reduced review scope.

Compare post-editing and retranslation without making the test misleading

Choose a mixed sample covering the actual subject matter, long and short segments, terminology density, tables and awkward source passages. Separate materially different language pairs and content types. Record why each part of the sample belongs.

Have appropriately qualified linguists work to the same acceptance criteria with equivalent context and resources. Avoid having someone post-edit a passage and then immediately translate that identical passage from scratch. Their earlier reading will influence the second timing.

Use matched portions or counterbalance the order across participants where practical. Record the limitations if a small team cannot control every variable. A pilot estimates your workflow; it does not need to pretend to be a universal benchmark.

  • Measure source reading and terminology research.
  • Measure target correction or fresh drafting.
  • Include the planned independent review and final checks.
  • Record file preparation, queries and required reporting.
  • Note interruptions, uncertainty and passages that exceed the proposed scope.

A pilot can reveal that one method works for routine sections while another suits a difficult section. If you split the workflow, name the boundary and include the coordination cost. Do not assume that the linguist can switch methods without extra handling.

Show the cost of each route, including the hidden work

For each route, multiply the observed role-specific hours by your actual agreed costs. Add the actual platform, preparation and handling costs. Apply your business's chosen pricing policy explicitly; a desired margin and a markup on cost are different calculations.

Do not extrapolate the sample mechanically across a heterogeneous book or multilingual programme. Estimate separately where languages, genres, draft provenance or requirements differ. Give the client a range when the remaining input is uncertain.

If a fixed per-word quote is commercially useful, derive it from that effort estimate and define its assumptions. If the client cannot provide representative input, consider a paid assessment or an hourly cap before a fixed commitment.

Two bases for a post-editing quote
Discount by default
  • The existence of a machine draft sets the rate.
  • Only changed words appear as effort.
  • Extra explanations and source updates stay implicit.
Estimate the agreed workflow
  • A pilot tests whether the draft saves time.
  • Reading, revision and reporting enter the estimate.
  • The quote identifies versions, exclusions and a review checkpoint.

A small edit can require a large amount of checking

A reviewer might spend several minutes checking a single number or a subtle qualifier, then make a one-character change. Another segment may need many mechanical changes that are straightforward. Edit counts describe the result of editing, not the full process.

The original research paper The Trials and Tribulations of Predicting Machine Translation Post Editing Productivity explicitly distinguishes edit distance from cognitive effort and time. Its study reports useful relationships in its data, but that does not make a universal tariff or predict your next language pair.

Use edit distance alongside time, observed defects and final review outcomes. If someone changes very little, inspect whether the input was good or whether a difficult issue went unnoticed. If they change a lot, inspect whether those edits were necessary under the brief.

The checkpoint when the estimate stops matching reality
  1. Observe the mismatch

    The production content takes materially more effort or differs from the sampled input.

  2. Capture the evidence

    Record affected material, reason and observed time without exposing client data.

  3. Pause for a decision

    Agree a revised scope, method, budget or schedule with the accountable client owner.

  4. Resume with a new baseline

    Record the approved change and review the next comparable batch.

This checkpoint protects both sides. The client can decide whether the additional quality requirement is needed, and the LSP can describe the work before it becomes an invoice dispute. Record the agreed threshold in the quote rather than inventing it halfway through.

Give account managers a repeatable intake checklist

Before accepting a discounted post-editing job
  • Get representative source and draft content with permitted access.
  • Define the required quality, context and acceptance owner.
  • Check the basis of any translation-memory discounts.
  • Compare methods on equivalent material and conditions.
  • Include research, independent review and reporting.
  • Record scope, file versions and assumptions in the quote.
  • Agree when production pauses for a change decision.
  • Compare the estimate with actual effort after delivery.
Download this checklist (PDF)

Store the pilot result with the quote so production can see how the estimate was made. Keep language, domain, method and required output attached to the timing. A reusable rate card should retain those boundaries instead of averaging away the difficult work.

If your enquiry process cannot capture these inputs, use a discovery call to map one quote from intake to delivery. A small assessment form or integration may remove repeated handoffs. The aim is a quote that production can execute and the client can understand.

Questions we hear

Is post-editing always faster than translating from scratch?

No universal result applies to every input. Draft quality, source difficulty, language pair, context and required output all matter. Compare the actual workflow on representative material. Include review and administration so a fast editing step does not hide a slower total job.

What rate should we charge for MTPE?

Use your actual role costs, business pricing policy and measured effort for the agreed output. There is no universal discount justified merely by an AI-generated draft. A fixed per-word fee needs stable assumptions; uncertain content may justify an assessment or an agreed hourly cap first.

Can translation-memory match percentages determine the review price?

They can inform the analysis when the origin and suitability of the stored translations are established. Similarity alone does not prove approval, context or effort. Include the match policy in the scope and test difficult cases before assuming that the same discount works across all content.

Sources

  1. Firsthand discussion of AI post-editing assignmentsLinkedIn
  2. Discussion of price pressure and sample-based demonstrationLinkedIn
  3. The Trials and Tribulations of Predicting Machine Translation Post Editing ProductivityLREC / ACL Anthology
Written by the SeriusTech engineering team

We build custom software, business systems, applied AI and localization technology for growing businesses. Every technical claim in this note was checked against the code it describes. Products and clients stay unnamed.

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