Methods
Omev NLP
Categories, entities, document sentiment, entity sentiment, moderation and a configured combined result.
Google Natural Language
Sentiment, entities, entity sentiment, syntax, content classification, moderation and annotateText.
Classify millions of documents without paying an LLM to read every page.
A lower-list-price Google Natural Language API alternative for repeated categorization, entity, sentiment and moderation workloads. Sentiment and entity extraction start at $0.50 per 1M Unicode characters.
Start with one batch your team has already reviewed. The output and monthly cost will tell you whether the workflow is worth moving.
$5 free credit · 10 days · no card
For SaaS products, publishers, marketplaces and platforms processing more websites, articles, reviews, tickets and posts than a team can read by hand.
Pay for the reading, not a general-purpose model writing one-word answers.
Most analysis calls do a small, repeatable job: return a category, find a name, score a sentiment or flag text for review. The work gets more expensive because customer activity grows, not because the task becomes harder.
OmevAI prices each function by Unicode character volume. Pick only the signals the product needs, see the monthly number before you integrate, and keep the current path connected while you test the output on texts your team has already reviewed.
Sentiment plus entity extraction plus entity sentiment costs $2.00 per 1M characters. One hundred million characters a month is $200.
What to measure
Judge the workflow by the work it removes—not by a demo score.
Start with a batch your team has already reviewed. Compare the output against the decisions people actually made, then watch these numbers in production.
Cost per 1M characters
The direct cost of the signals you selected, measured against the same volume on the current path.
Manual review time
How many hours the team spends sorting, tagging and preparing the same volume of text before and after the move.
Agreement on known texts
How often the output matches the labels your team already accepted—and where the disagreements cluster.
Useful coverage
The share of incoming text that reaches the right dashboard, queue or owner without a manual first read.
Cost per customer
The analysis bill divided by active accounts, so growth does not quietly erase product margin.
What does analysing your text volume cost?
Enter the number and average length of the texts you receive, then select the signals your product needs. The estimate uses the published OmevAI rate for each selected function.
Monthly text volume
100,000,000 characters
Estimated Omev cost per month
$200
Sentiment$50.00
Entities$50.00
Entity sentiment$100
$5 free credit · 10 days · no card
How this estimate works
Monthly characters equal text count multiplied by average characters per text. Each selected function is priced separately against that same character volume using the OmevAI list rates shown on this page. The estimate does not assume retries, taxes or a private contract rate.
Google NLP vs OmevAI NLP
Lower list price does not mean identical APIs.
Both services can classify text, find entities, measure sentiment and flag content for review. The important differences are the taxonomy, response shape, billing model and production fit—not the feature names alone.
Decision
Omev NLP
Google Natural Language
Compatibility
Omev NLP
Not a drop-in Google replacement. Map the selected fields once and move one analysis function first.
Google Natural Language
Keep the existing Google response shape when your product already depends on it.
Taxonomy
Omev NLP
Use the categories your product, queue or reporting system already understands.
Google Natural Language
Content classification uses Google's supported content-category taxonomy.
Pricing
Omev NLP
Flat public rates per 1M Unicode characters. Sentiment and entities are $0.50 each; select only the functions you need.
Google Natural Language
Feature-specific rounded units, monthly free allowances and lower rates at higher volume can change the final bill.
Latency
Omev NLP
No universal latency claim. Measure the selected signals on your real payload sizes before moving production traffic.
Google Natural Language
Benchmark the same requests in the region and architecture your application will actually use.
Limits
Omev NLP
Confirm throughput, batch size and every required language during the evaluation.
Google Natural Language
Check the current project quotas, request rules and language matrix for every feature you use.
This is a buying summary, not a parity claim. Response fields, languages, request behavior and production limits must pass on your own dataset before any route moves.
Read the full Google NLP comparison →Automate the first read. Keep the decisions with your team.
OmevAI turns each text into structured signals. Your product still decides what those signals do.
Keep human-owned
- Define the categories that matter to the business and what should happen after each one.
- Write the reply, product decision or policy action that follows the analysis.
- Review unusual or high-impact cases where a wrong label costs more than a manual check.
- Make the final moderation decision. The API can build the queue; it should not replace your policy.
Automate the first read
- Classify every review, support ticket and post into the topics your team tracks.
- Extract the products, brands, people and places customers mention.
- Measure sentiment for the whole text or for each entity inside it.
- Tag content that should enter a human moderation queue.
- Backfill an unread archive so the first report covers more than last week.
Eight text-analysis workflows that get more expensive as your volume grows.
Start with the workflow that already has a clear label set, review queue or dashboard waiting for the output.
Support and feedback routing
Put every ticket, review or survey answer into an agreed category for $1.00 per 1M characters. The team sees the right queue instead of one shared backlog.
Voice-of-customer dashboards
Extract the products, features and competitors people mention for $0.50 per 1M characters, then add sentiment to each one for another $1.00.
Review and marketplace intelligence
Measure overall sentiment for $0.50 per 1M characters, then split it by product, seller, market or category using the entities in the same dataset.
User-generated content review
Tag text that should be reviewed for $2.50 per 1M characters. OmevAI helps order the queue; your policy and team make the final decision.
Historical backfills
Run the same analysis over years of tickets, reviews or comments so a product decision starts with the whole archive—not whichever sample somebody had time to read.
Website and article categorization
Assign websites, landing pages and articles to the taxonomy your directory, publisher or discovery product already uses for $1.00 per 1M characters.
Large-scale web corpus processing
Run one consistent set of categories, entities and sentiment signals across a crawl or document collection instead of paying a general-purpose LLM to reason through every page.
Content enrichment for search and discovery
Add topics, entities and sentiment to each document so search, related-content modules and internal reports can work from structured fields rather than raw text.
What this looks like in production.
One review, three product decisions
“Reporting is finally useful, but the Business plan signs me out and the Team plan is too expensive.” A single overall sentiment score calls that review mixed and stops there.
Entity sentiment separates Business plan / reporting / positive, Business plan / session handling / negative and Team plan / price / negative—three rows that can reach three owners.
A moderation team sees what needs attention first
A marketplace receives posts, comments and profile updates faster than a small team can read them. User reports reveal only the share somebody noticed.
OmevAI tags content for review and sends the reason into the queue. The team still applies the policy and makes the final decision.
The quarterly support review stops being a sample
Instead of asking two people to skim a few hundred tickets, run the complete quarter through the same categories and entity list.
The report shows which problem appears most, which product or integration it affects and whether the pattern is improving across quarters.
How much has to change.
Choose one real dataset and the signals you want back. Create a key, run the same texts through OmevAI and compare the result with the labels your team already accepted.
Your dashboard, queue and business rules stay where they are. Map the returned fields once, keep the old path as fallback and move more traffic only after the output holds up on your data.
Read the API docs →What it costs.
Every function has a public rate per 1M Unicode characters: categories $1.00, sentiment $0.50, entities $0.50, entity sentiment $1.00 and moderation $2.50. Select only what the workflow needs; the calculator above shows the combined monthly cost.
Categories
$1.00 per 1M Unicode characters
Route reviews, tickets and posts into the topics your team tracks.
Sentiment
$0.50 per 1M Unicode characters
See whether each text reads as positive, negative or mixed.
Entities
$0.50 per 1M Unicode characters
Pull out the products, brands, people and places being discussed.
Entity sentiment
$1.00 per 1M Unicode characters
Attach sentiment to each named product, feature or competitor.
Moderation
$2.50 per 1M Unicode characters
Tag text that should enter a human review queue.
List prices, checked 21 September 2026 · NLP rate comparison
What we can actually prove.
Every claim below is either arithmetic on published rate cards or a fact you can check. We do not publish quality benchmarks we ran on ourselves — we run yours instead.
Sentiment and entity extraction are each $0.50 per 1M characters—half Google's first paid-tier unit rate before Google's free allowance and volume discounts.
How this is supported
OmevAI list price is $0.50 per 1M Unicode characters for each function. Google publishes $1 per 1,000 units in its first paid tier, with one unit equal to up to 1,000 Unicode characters for those features. Google's free allowance, per-request rounding and lower high-volume tiers can change the invoice, so compare your own request pattern rather than treating the unit-rate difference as a guaranteed saving.
Moderation is $2.50 per 1M characters. Google's first paid-tier unit rate works out to $50 per 1M characters before its free allowance and volume discounts.
How this is supported
Google bills moderation in 100-character units at $5 per 1,000 units in its first paid tier, which is $50 per 1M characters before the monthly free allowance. Google then publishes lower rates at higher volume. OmevAI's published moderation rate is $2.50 per 1M Unicode characters. This is price arithmetic only, not a claim of equal coverage or accuracy.
Entity sentiment turns one mixed paragraph into separate signals for each product, feature or competitor it names.
How this is supported
This is a statement about the output shape, not an accuracy score. Run a labelled batch from your own product and inspect the disagreements before changing the production route.
The five prices on this page come from one shared rate table used by the cards and calculator.
How this is supported
Categories $1.00, sentiment $0.50, entities $0.50, entity sentiment $1.00 and moderation $2.50 per 1M Unicode characters, checked 21 September 2026. The page does not reuse text-generation token rates for analysis work.
Check the comparison
The Google comparison uses Google's own rate card.
Google includes monthly free allowances, per-request rounding and lower rates at higher volume. Those details matter, so the full comparison separates unit price from the bill your request pattern produces.
OmevAI NLP vs Google Natural Language API ↗A feature-by-feature comparison with the pricing caveats kept visible.Google Cloud Natural Language pricing ↗Google's official units, free allowances and volume tiers.Google annotateText documentation ↗Google's official description of the features available in a combined request.
Questions before you move the first batch.
What does this cost?
Categories and entity sentiment are $1.00 per 1M Unicode characters. Sentiment and entity extraction are $0.50 each. Moderation is $2.50. If one text needs three functions, each selected function is priced against that text volume; use the calculator above for the combined monthly number.
How do we know it is accurate?
Run a batch your team has already labelled. Compare the outputs, inspect where the two disagree and decide which errors are acceptable for this workflow. We do not publish a universal accuracy score because your categories, language mix and text are what decide whether it works.
Do we have to replace our current NLP or LLM provider?
No. Start with one dataset or one call type and keep the current route as fallback. Move more traffic only after the returned fields work with your dashboard or queue.
Can we use our own categories?
Yes. Bring the category list your team already uses and include the ambiguous examples people disagree about. If the list changes later, re-run the relevant history so old and new reports still mean the same thing.
Does moderation remove content automatically?
No. OmevAI tags text so your team can review the right items first. Your policy decides whether anything is hidden, removed or escalated.
Will our historical reporting still line up?
Test that separately from accuracy. Run OmevAI and the current path on the same period, compare the distribution of labels and re-annotate history if a supplier change would otherwise appear as a fake trend.
How is this different from sending the text to a general LLM?
A general LLM can return the same kinds of labels, but it is priced and designed for much broader work. OmevAI NLP gives these repeated analysis jobs their own functions, character-based rates and predictable output shape.
Other use cases
Bring one labelled batch. See the output and the real monthly cost.
Register with your work email, choose the signals you need and run the texts your team already knows. Move nothing until the result holds up.
$5 free credit · 10 days · no card · Keep your current provider connected