NLP & Linguistic Services
Our mission is to empower the next generation of AI by delivering high-quality, multilingual, and human-verified data solutions. We help companies build smarter, fairer, and more inclusive technology.
POS Tagging
At Jeenish AI Solutions, we provide Part-of-Speech (POS) tagging, which involves labeling each word in a sentence with its grammatical role—such as noun, verb, adjective, or adverb. This is a foundational step in natural language processing (NLP) that helps machines understand sentence structure and meaning. POS tagging supports a wide range of applications including machine translation, speech recognition, and information extraction. Our native-linguist teams handle multilingual POS tagging with high linguistic accuracy. This service is especially useful in sectors like legal tech, healthcare documentation, and conversational AI, where understanding context is critical.
Request a DemoLemmatization & Tokenization
At Jeenish AI Solutions, we provide lemmatization and tokenization services to prepare raw text for deeper linguistic analysis. Tokenization involves splitting sentences into individual words or phrases (tokens), while lemmatization reduces words to their base form—like converting “running” to “run” or “cars” to “car.” These processes are essential for powering natural language processing tasks such as search engines, chatbots, and document classification. We support multilingual tokenization and lemmatization, tailored to complex domains like healthcare or legal text. Our expert annotators and linguists ensure high consistency, enabling your models to extract meaningful insights from structured text.
Sentiment & Intent Annotation
At Jeenish AI Solutions, we specialize in sentiment and intent annotation to help AI systems understand not just what is said, but how it’s said and why. Sentiment annotation involves labeling text as positive, negative, or neutral, while intent annotation captures the purpose behind the message—like asking a question, making a purchase, or filing a complaint. These annotations are critical for training chatbots, voice assistants, social media monitoring tools, and customer support analytics. For example, tagging tweets to track public opinion or classifying customer emails by urgency and intent Our multilingual teams ensure cultural sensitivity and contextual accuracy, delivering labeled datasets that enhance natural language understanding across domains.
Request a DemoText Classification
At Jeenish AI Solutions, we offer text classification services that involve categorizing text into predefined labels—such as topic, intent, or urgency. This allows AI systems to efficiently organize, filter, and respond to vast volumes of textual data.
It’s commonly used in applications like spam detection, content moderation, customer support ticket sorting, and news categorization. For example, classifying a user’s review as feedback related to “delivery,” “product quality,” or “customer service.”
We support multi-class and multi-label classification in multiple languages, ensuring consistent, high-accuracy results across diverse industries and use cases.
Text Summarization Tagging
At Jeenish AI Solutions, we offer text summarization tagging services that involve annotating source text alongside its concise summaries. This helps train models to understand key information and generate accurate, human-like summaries. It’s widely used in news aggregation, legal case briefings, medical reports, and document search engines. For example, a long product review can be tagged with a 2-line summary that captures the main sentiment and issues mentioned. Our linguists ensure that summaries retain factual accuracy and contextual relevance, supporting both extractive and abstractive summarization models in multiple languages.
Request a DemoClean & Timestamped Transcription
At Jeenish AI Solutions, we provide clean and timestamped transcription services that convert audio or video content into structured, readable text. "Clean verbatim" transcription excludes fillers and false starts for clarity, while timestamps mark when each sentence or speaker segment occurs. This service is essential for training speech recognition systems, building subtitle datasets, and analyzing call center recordings. For instance, transcribing customer support calls with speaker labels and timecodes helps train AI for automated QA. We support multilingual transcription with speaker identification and deliver high-accuracy, time-aligned text tailored for your AI pipeline.
Multilingual Translation
At Jeenish AI Solutions, we offer multilingual translation services that go beyond direct word-for-word conversion. Our native-language experts ensure that translations are contextually accurate, culturally appropriate, and tailored to the domain—be it medical, legal, e-commerce, or conversational AI.
We support over 30 global languages, enabling your AI systems to function effectively across markets. This service is vital for training multilingual chatbots, cross-border content moderation, and inclusive digital platforms.
Each translation is quality-checked and can be paired with annotations like speaker tags, intent labels, or sentiment to enrich your datasets further.
Request a DemoLLM Output Evaluation & Correction
At Jeenish AI Solutions, we provide LLM output evaluation and correction services to ensure your large language model generates accurate, relevant, and bias-free responses. Our expert reviewers assess model outputs for factual correctness, coherence, tone, and ethical alignment.
This is essential for applications like chatbots, virtual assistants, summarization tools, and content generation platforms. For instance, we help fine-tune models by identifying hallucinations or culturally inappropriate responses and providing human-corrected alternatives.
With multilingual support and domain-specific expertise, we help you build trustworthy, production-ready LLM applications.
Contextual Data Localization
At Jeenish AI Solutions, we offer contextual data localization to adapt content not just linguistically, but culturally and contextually for specific regions or audiences. This involves modifying language, references, formats, idioms, and even visuals to make data resonate locally—without altering its original intent.
It’s crucial in training AI for multilingual chatbots, global voice assistants, and cross-border recommendation systems. For instance, converting a health app’s English dataset into culturally accurate Hindi or Spanish content for localized deployment.
Our native linguists and annotators ensure every localized dataset maintains clarity, compliance, and user relevance across 30+ languages. Request a DemoAudio Annotation
At Jeenish AI Solutions, our voice-to-text transcription service converts spoken language from audio files into accurate, structured written text. This is essential for training voice assistants, speech recognition models, and audio analytics systems.
We handle clean verbatim transcription—removing fillers and repetitions—for clarity, or full verbatim if required. Timestamps and speaker labels are added to support easy reference and training alignment.
Used in domains like customer support, healthcare dictation, media captioning, and meeting analysis, our multilingual transcription teams ensure high-quality, consistent outputs for global use cases.
Audio Segmentation
At Jeenish AI Solutions, we offer audio segmentation services that divide long audio files into meaningful segments based on changes in speaker, topic, or silence. This is crucial for preparing data for speech recognition, diarization, and voice assistant training.
For example, in call center recordings, we segment conversations by speaker turns or issue types to make downstream labeling more manageable. In podcasts or interviews, segmentation helps isolate individual questions or topics.
Our team uses a mix of automated tools and human validation to ensure precise, context-aware segmentation—supporting multilingual datasets across industries like customer service, media, and healthcare.
Request a DemoSpeaker Diarization (Labeling)
At Jeenish AI Solutions, we provide speaker diarization services that identify and label "who spoke when" in multi-speaker audio recordings. This process segments audio by speaker and assigns consistent speaker IDs across the file, even when names are unknown.
It's essential in call center QA, courtroom recordings, podcast editing, and meeting transcription—where knowing who said what matters as much as what was said. For instance, separating a support agent’s and customer’s dialogue allows clearer insights into conversation flow.
Our multilingual annotators ensure accurate speaker boundaries and consistent labeling, even in overlapping or noisy audio environments.
Emotion & Tone Tagging
At Jeenish AI Solutions, we offer emotion and tone tagging to identify and label the emotional state or tone expressed in audio clips—such as happy, angry, frustrated, calm, or neutral. This helps AI systems interpret not just words, but how they're said.
This service is widely used in sentiment-driven applications like customer support analysis, conversational AI, mental health tools, and smart assistants. For example, detecting frustration in a customer’s voice can trigger real-time escalation or adaptive responses.
Our annotators are trained to handle nuanced expressions across languages and cultures, ensuring that models are emotionally intelligent and context-aware.
Request a DemoMultilingual Audio Processing
At Jeenish AI Solutions, we provide multilingual audio processing to transcribe, annotate, and analyze spoken content across 30+ languages and dialects. This enables voice AI systems to operate accurately in diverse linguistic and cultural contexts.
Our services include speaker labeling, transcription, emotion tagging, and segmentation—all performed by native-language experts. For instance, annotating customer calls in Spanish, Hindi, or Arabic for intent and tone improves multilingual virtual assistants.
We ensure language-specific nuances, accents, and cultural expressions are accurately captured, delivering high-quality datasets for global AI applications in CX, healthcare, media, and more.