7 Best APIs for Language-Detection in Nigeria

Detect Language API is a language identification service that analyzes text input and returns the language it is written in, along with a confidence score, from a library of over 164 supported languages. Unlike translation APIs that convert text between languages, language detection is the prerequisite step — identifying what language the text is in before deciding what to do with it. The API is particularly valuable for Nigerian applications because it supports language detection for Yoruba, Igbo, and Hausa — Nigeria's three most widely spoken indigenous languages — as well as Nigerian Pidgin English. This enables Nigerian platforms to build genuinely multilingual experiences where user-submitted content is automatically identified by language and routed appropriately. The detection algorithm analyzes statistical patterns in the text — character frequency distributions, word patterns, and n-gram features — to identify the most likely language. For most languages with sufficient text, detection accuracy exceeds 95%. The API returns both the top match and alternative candidates with their respective confidence scores, allowing applications to handle ambiguous cases (such as very short texts or mixed-language content) with appropriate fallback behavior. Batch detection mode accepts multiple text strings in a single API call and returns language identifications for each, making it efficient for processing content in bulk — categorizing a backlog of user-generated posts, classifying customer messages, or tagging a database of documents by language. For Nigerian social media platforms, community forums, and content sharing applications, language detection enables dynamic routing and display logic. When a user posts in Yoruba, the platform can tag the post with its language, surface it to Yoruba-speaking users in their personalized feed, and potentially offer auto-translation for non-Yoruba speakers. Without automatic language detection, this requires manual tagging by moderators — an approach that does not scale. Nigerian customer support systems receive incoming messages in multiple languages. A support platform that can automatically detect whether an incoming message is in English, Yoruba, Igbo, Hausa, or Pidgin and route it to the appropriate language-capable agent provides significantly better customer experience than requiring all customers to write in English. Detect Language API makes this routing logic straightforward to implement. Nigerian news aggregators and media platforms that collect content from diverse sources can use language detection to categorize articles by language — enabling language-filtered views, language-specific newsletters, and content recommendation that respects language preferences. The API pricing starts at just $4.95/month for 100,000 detections per day, making it very affordable for Nigerian startups and SMEs. The REST API interface is simple — send text, receive language code and confidence score — and client libraries are available for Python, PHP, Ruby, JavaScript, Java, Go, and other languages. Authentication uses a simple API key passed in the Authorization header, and the free tier provides 1,000 detections per day — sufficient for development and low-volume production use. Detect Language API's multilingual detection handles code-switched text — content where a writer switches between languages mid-document or mid-sentence, common in Nigerian social media where Yoruba or Igbo phrases are embedded in otherwise English posts. While perfect code-switching detection is challenging for any system, the API's confidence scoring helps applications identify when text contains mixed-language content that may benefit from human review or special handling rather than automatic routing. The API maintains a detection threshold — minimum confidence level below which it returns null rather than a low-confidence prediction. Nigerian applications can configure their handling of null responses (falling back to a default language, requesting user confirmation, or tagging content for human review) to ensure that ambiguous cases do not produce incorrect downstream actions.

Cloudmersive NLP API is a comprehensive natural language processing service that provides developers with a wide range of text analysis, transformation, and content moderation capabilities through a simple REST API. Cloudmersive stands out in the NLP API market through its exceptionally generous free tier of 50,000 API calls per month, making enterprise-grade text analysis accessible to Nigerian startups, independent developers, and small teams without requiring NLP research expertise or significant data budgets. The API provides sentiment analysis that evaluates text as positive, negative, or neutral with confidence scores. Unlike basic rule-based sentiment tools, Cloudmersive uses machine learning models trained on large text corpora to detect nuanced sentiment signals, including sarcasm and implied negativity that simpler systems miss. For Nigerian customer service platforms and social media monitoring tools, accurate sentiment detection translates to better understanding of customer feedback and public opinion about brands and products. Language detection identifies the language of a text sample from over 50 supported languages, returning the detected language and confidence score. For Nigerian platforms handling user-generated content from diverse sources — including content in English, French, Portuguese for diaspora users, and potentially Nigerian languages — automatic language detection enables routing content to appropriate processing pipelines and moderation queues. Entity extraction identifies named entities in text including people, organizations, and locations. This structured data extraction from unstructured text supports applications that need to understand what a piece of content is about without reading it manually. Nigerian news aggregators and media monitoring services can use entity extraction to automatically index which companies, politicians, and geographic areas are discussed in incoming content. Profanity and hate speech detection is a critical content moderation capability for platforms hosting user-generated content. The Cloudmersive API includes endpoints for detecting offensive language, hate speech, and inappropriate content, enabling Nigerian social platforms, forum operators, and comment section managers to automatically filter or flag problematic content before it becomes visible to other users. As Nigerian online communities grow, automated content moderation becomes essential for maintaining healthy platform environments. Similarity detection compares two pieces of text to determine how semantically similar they are. This capability powers duplicate content detection, plagiarism checking, and fuzzy matching applications. Nigerian educational institutions can use similarity detection to identify copied student submissions, while Nigerian news platforms can detect when content has been republished from other sources. Text transformation features include rephrasing, summarization assistance, and extraction of key sentences from longer documents. These capabilities help Nigerian productivity applications that need to compress lengthy documents into digestible summaries or identify the most important sentences in research materials. Part-of-speech tagging and dependency parsing provide grammatical analysis of text, identifying nouns, verbs, adjectives, and the relationships between them. These linguistic features support advanced text analysis applications including information extraction systems and structured data derivation from unstructured text. The 50,000 free monthly API calls represents an extraordinary entry point for Nigerian developers — this volume accommodates processing tens of thousands of text samples monthly without spending a naira on API costs. For applications processing user comments, product reviews, customer support tickets, or social media mentions, 50,000 calls per month supports meaningful production usage at small to medium scale. Paid plans scale the call limit for growing applications. API key authentication and clear JSON responses make integration rapid and predictable for Nigerian development teams across all frameworks and programming languages.

The Code Detection API is a programming language identification service that analyzes code snippets and determines which programming language they are written in. Hosted on RapidAPI, the service supports over 40 programming languages and returns a confidence score alongside the detected language, enabling applications to handle multi-language code inputs intelligently. The API solves a common problem in developer tools and coding platforms: when users submit code without specifying the language, the application needs to automatically identify it to apply appropriate syntax highlighting, execute it with the correct runtime, route it to language-specific validators, or tag it for categorization. Manual language specification is unreliable — users forget, mislabel, or do not know how to categorize their code — making automatic detection essential for a seamless experience. The detection works by analyzing the syntactic patterns, keywords, structure, and character-level features of the submitted code snippet. Even relatively short snippets (20-50 lines) provide enough signal for accurate detection in most languages. The confidence score indicates the certainty of the detection, allowing applications to display results with appropriate confidence caveats or request manual confirmation for low-confidence detections. Supported languages span the full range of widely-used programming and scripting languages, including Python, JavaScript, TypeScript, Java, C, C++, C#, Go, Rust, PHP, Ruby, Swift, Kotlin, R, MATLAB, SQL, HTML, CSS, Shell, and many others. This breadth makes the API useful for platforms that serve diverse developer communities working across different technology stacks. For Nigerian developer community platforms and Q&A sites, automatic code detection enables better content organization. When a user posts a code question without tagging it with a language, the platform can auto-tag it — improving searchability, enabling language-specific filtering, and routing the question to community members who specialize in that language. Nigerian developer communities on platforms like Slack, Discord, or custom forums benefit from automated language tagging of shared code. Nigerian online coding bootcamps and educational platforms that offer open-ended coding exercises (where students can solve problems in any language) benefit from automatic language detection to route solutions to appropriate test runners and evaluation systems. Rather than requiring students to specify which language they used, the platform detects it and applies the correct grading logic. Nigerian developer portfolio and hiring platforms that analyze candidate code submissions for skills assessment can use Code Detection API to automatically categorize code samples by language — building accurate skill profiles without relying on candidates to self-report their language expertise. The API is hosted on RapidAPI, requiring a RapidAPI subscription and the X-RapidAPI-Key header for authentication. The free tier provides limited monthly requests suitable for development and low-volume use. REST calls accept code as a request parameter and return the detected language and confidence score as JSON. Code Detection API's output includes not just the top-detected language but also a ranked list of alternative language candidates with their respective confidence scores. For ambiguous code snippets — very short fragments, polyglot files, or code that uses syntax common to multiple languages — the ranked alternatives allow applications to handle uncertainty gracefully, potentially showing the top two or three candidate languages to the user for manual confirmation. The API handles common syntax patterns that appear across languages, using statistical and pattern-based analysis to discriminate between similarly-structured languages like Java and C#, or Python 2 and Python 3. This discriminative capability is important for Nigerian developer platforms where distinguishing between closely related languages affects routing, syntax highlighting, and tool selection.

Tisane Text Analysis API is a specialized multilingual natural language processing service focused on deep linguistic analysis, content safety detection, and entity extraction across over 30 languages. Unlike general-purpose NLP APIs that offer surface-level text classification, Tisane performs full grammatical analysis including part-of-speech tagging, dependency parsing, and semantic role labeling, enabling applications that need to understand not just what a text is about but how its meaning is constructed. The abuse and content safety detection capabilities are among the most advanced features. Tisane classifies harmful content into fine-grained categories: personal attack, bigotry, criminal activity, sexual advances, mental abuse, and self-harm — going significantly beyond a binary "toxic/not toxic" classification. Each detected issue is returned with the offending text span, category label, severity score, and offset position in the input string, enabling targeted responses like masking specific words rather than rejecting entire messages. This granularity is valuable for Nigerian social platforms that want nuanced moderation — warning a user about a borderline comment rather than immediately banning them. Entity extraction identifies named entities (people, organizations, locations, dates, products, currencies) with type labels and optional enrichment from linked databases. For Nigerian news platforms, entity extraction can automatically tag articles with relevant people, organizations, and locations, building a structured knowledge graph from unstructured text. This powers features like "see all articles mentioning GTBank" or "all news about Lagos State" without manual tagging by editors. Sentiment analysis returns document-level and aspect-level sentiment — understanding that a restaurant review might express positive sentiment about the food but negative sentiment about the service requires aspect-based analysis that sentence-level or document-level models miss. Nigerian businesses that aggregate customer reviews can use aspect-level sentiment to identify specific product or service attributes that customers love or complain about. Language detection identifies the language of input text, critical for Nigerian platforms where users write in English, Yoruba, Igbo, Hausa, and Nigerian Pidgin. The API handles code-switching (mixing languages within a single sentence), which is common in Nigerian social media communication. Tisane's sentiment analysis returns both document-level and entity-level sentiment scores. At the entity level, the API identifies named entities within the text (people, organizations, products, locations) and returns a sentiment polarity score specifically for how the text refers to each entity. This is a significant technical advantage over document-level sentiment analysis — a product review might express positive sentiment overall while containing negative sentiment toward a specific feature. Nigerian product teams and customer success platforms can use entity-level sentiment to identify specific product attributes drawing negative feedback without manual review. The rule-based approach for many of Tisane's classifiers also makes behavior more predictable and explainable compared to purely neural models, which is important for applications in regulated industries. Tisane's language detection handles texts as short as a single sentence reliably, which is important for social media and messaging contexts where individual short messages need to be identified before routing to the appropriate language-specific moderation model. Nigerian platforms serving multi-lingual communities where short comments might be in any of several languages benefit from accurate short-text language detection.

Lecto Translation API is a fast, affordable machine translation service supporting over 90 languages, with a particular distinction for Nigerian developers: it includes support for Yoruba, Igbo, and Hausa — the three largest Nigerian languages by speaker count. This makes Lecto one of the few translation APIs that enables developers to build genuinely multilingual applications for Nigerian audiences. Nigeria is a linguistically diverse nation with over 500 languages, and while English is the official language, a significant portion of the population is more comfortable communicating in Yoruba, Igbo, Hausa, or Pidgin. Applications that serve broad Nigerian audiences — from government services to fintech apps to consumer platforms — increasingly need multilingual support to be truly accessible and to deliver services to citizens in their preferred language. The translation API accepts text input in a source language and returns translated text in the target language. Batch translation mode allows multiple strings to be translated in a single API call, which is efficient for translating UI text arrays, product description lists, or notification templates in bulk. Automatic language detection can identify the source language if it is not specified, though specifying the source language improves accuracy and performance. For Nigerian edtech platforms, Lecto enables translation of learning content into Yoruba, Igbo, or Hausa — making educational materials accessible to students whose primary language is not English. This is particularly valuable for early childhood education, adult literacy programs, and agricultural extension services that reach rural populations. Nigerian fintech and banking applications serving customers across the country can use Lecto to translate customer communications, transaction notifications, and account statements into the customer's preferred language. A customer in Kano receiving SMS notifications in Hausa, or a customer in Ibadan receiving them in Yoruba, has a meaningfully better experience than receiving communications only in English. Nigerian e-commerce platforms can use Lecto to translate product descriptions, seller communications, and customer support responses — enabling buyers and sellers who prefer Yoruba, Igbo, or Hausa to participate fully in the marketplace without language being a barrier to commerce. The API is hosted on RapidAPI, which provides a unified authentication flow using the X-RapidAPI-Key header. The competitive pricing — starting at $9.99/month for 500,000 characters — makes it accessible for Nigerian startups and SMEs that need translation capabilities without the budget for enterprise translation services. Integration requires a RapidAPI subscription to the Lecto Translation endpoint. REST calls with JSON body containing the source text and target language return translated text in the response. The API's simplicity means integration can be completed in a few hours with any HTTP-capable backend. Lecto Translation API's batch mode processes multiple text strings in a single API call, which is critical for efficient application localization workflows. Instead of calling the API once per UI string (which would be hundreds of calls for a typical application), the full set of strings requiring translation can be submitted in one batch, dramatically reducing API call overhead and latency. The API's support for HTML content translation preserves HTML markup in the source text — translating only the visible text content while leaving HTML tags, attributes, and structure intact. This is essential for Nigerian developers translating web content where the markup structure must survive the translation process without corruption. Lecto's competitive per-character pricing makes it economical for Nigerian developers with budget constraints. At small volumes, monthly costs remain manageable even for applications with significant translation requirements — enabling Nigerian startups to launch multilingual products without enterprise translation service budgets.