Leverage Trellis Data's expertise in fine-tuning AI for translation and transcription. Our specialists design and optimize models to handle bespoke languages and dialects, delivering accurate, context-aware results where off-the-shelf tools fall short.
Trellis Data addresses the limitations of off-the-shelf translation and transcription tools by developing custom AI solutions capable of understanding and processing bespoke languages.
We create production ready models that bridge the gap where mainstream options fall short, equipping enterprises, government agencies, and high-security organizations with language solutions tailored to their unique needs and use cases.
We specialize in training, fine-tuning, and optimizing speech-to-text AI models, ensuring accurate output for niche, low-resource, or specialized languages. Our models are designed to deliver optimal results, while providing the linguistic accuracy and cultural sensitivity required for mission-critical applications. Our models are already deployed and trusted by law enforcement and high security agencies in government.
Our transcription models run much faster than real time (depending on the underlying GPU hardware you choose); this means the price per hour of processed audio is much lower than the price to run the model for an hour. We support batched and realtime operation so you can optimize appropriately to your needs.
Highlights
Accurate transcription with preprocessing aimed at handling a variety of audio sources.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
You pay by the hour for each host that runs the English speech transcription model. Pricing is organized by two choices. First, you pick an AWS instance type: ml.g4dn.xlarge, ml.g5.xlarge, ml.g6.xlarge, or ml.m5.xlarge. These differ in compute power, so hourly rates vary. Second, you pick a processing mode. Real-time mode transcribes as audio arrives and is available on all four instance types. Batch mode processes stored audio in groups and is available on ml.g5.xlarge and ml.m5.xlarge. Costs scale with how many hours each host runs.
Top-of-mind questions for buyers
What am I billed for on each host per hour?
You pay for each host instance while it runs the transcription model, measured in host hours. Billing meters running time. A host that is fully stopped does not accrue software charges. Underlying AWS storage or other resource fees may still apply while an instance is stopped.
How does batch mode differ from real-time mode for my costs?
Real-time mode transcribes audio as it streams in, so the host runs continuously while you listen. Batch mode processes stored audio files in groups, so the host runs only during processing jobs. Real-time suits live audio; batch suits recorded files processed later.
If I run more audio, what drives up my bill?
Your bill scales with host hours, not the amount of audio itself. The instance type sets the hourly rate, and the number of hours each host runs sets total cost. Running more hosts or longer sessions raises charges. Each running host meters independently.
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Vendor refund policy
Refund Policy (Effective: 09/10/2026)
Refunds for Trellis Data Speech Transcription models may be granted for technical issues unresolvable by support, billing errors, or duplicate charges. Services already rendered, custom configurations, or costs from customer misuse or misconfiguration are non-refundable. This policy operates per AWS Marketplace terms. Contact: support@trellisdata.com.au (9AM-5PM AEDT, weekdays). Policy subject to updates.
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An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Real-time inference
Deploy the model as an API endpoint for your applications. When you send data to the endpoint, SageMaker processes it and returns results by API response. The endpoint runs continuously until you delete it. You're billed for software and SageMaker infrastructure costs while the endpoint runs. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Deploy models for real-time inference .
Batch transform
Deploy the model to process batches of data stored in Amazon Simple Storage Service (Amazon S3). SageMaker runs the job, processes your data, and returns results to Amazon S3. When complete, SageMaker stops the model. You're billed for software and SageMaker infrastructure costs only during the batch job. Duration depends on your model, instance type, and dataset size. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Batch transform for inference with Amazon SageMaker AI .
Version release notes
Support for Sagemaker Invocations
Additional details
Inputs
Outputs
Usage instructions
Sample notebooks
Inputs
Summary
Supports file inputs with the following media types ['audio/wav', 'audio/mpeg']. For files larger than 30 seconds the model will split the audio into 30 second chunks for processing and provide the output per chunk.
Please include the content-type when sending a file for inference. See sample notebooks linked.
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Deepgram is the leading voice AI platform for enterprise use cases, offering speech-to-text (STT), text-to-speech (TTS), and full speech-to-speech (STS) capabilities. 200,000+ developers build with Deepgrams voice-native foundational models due to our unmatched accuracy, low latency, and pricing. Having processed over 50,000 years of audio and transcribed over 1 trillion words, there is no organization in the world that understands voice better than Deepgram.
Deepgram is the leading voice AI platform for enterprise use cases, offering speech-to-text (STT), text-to-speech (TTS), and full speech-to-speech (STS) capabilities. 200,000+ developers build with Deepgrams voice-native foundational models due to our unmatched accuracy, low latency, and pricing. Having processed over 50,000 years of audio and transcribed over 1 trillion words, there is no organization in the world that understands voice better than Deepgram.
Parakeet-tdt-0.6b-v2 is a 600-million-parameter automatic speech recognition (ASR) model designed for high-quality English transcription, featuring support for punctuation, capitalization, and accurate timestamp prediction.
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