Model as a Service
sations and developers to access, deploy, and use pre-trained AI models, including large language models (LLMs). Customers can immediately integrate capabilities like isiZulu or Swahili language processing into their own applications with a simple API call. This approach enables rapid integration of advanced AI capabilities into applications without the need to build, train, or manage models and infrastructure.
With MaaS clients receive a secure API key and can immediately integrate capabilities like isiZulu or Swahili language processing into their own applications with a simple API call. For our “Ready-to-Use AI Applications,” we build complete solutions, such as a customer service portal, that are powered by these NIMs on the backend. Interacts with the final application, while Cassava manages the scaling, security, and maintenance of the NIM microservices, delivering AI as a fully managed utility.
Fully Managed
The Maas handles all aspects of model hosting, scaling, maintenance, and updates. Users do not need to worry about provisioning servers, managing GPUs, or updating models as new research emerges. This reduces operational overhead, eliminates the need for in-house AI/ML infrastructure expertise, and ensures access to the latest model improvements and security patches.
Shared Access
The same model instance is made available to multiple customers through secure, isolated API endpoints. This multi-tenant approach maximises resource utilisation and cost efficiency.
Users benefit from economies of scale, as the cost of maintaining and updating the model is distributed across many customers. Underlying security and privacy controls ensure that data from different users is kept separate.
Provisioning Model:
On-Demand or Reserved
On-Demand: Instantly access models and pay only for what you use. This is Ideal for unpredictable or bursty workloads.
Reserved: Commit to a certain usage level or time period (e.g., annual plans) for discounted rates and guaranteed capacity. Suitable for production workloads with steady demand.
Foundational MaaS
Provides developers with an API key to access large-scale, general-purpose AI models such as the GPT family of models by Open AI, Claude by Anthropic and Google’s Gemini.
Models under this category have been pre-trained on broad, general tasks like text generation, summarization, and reasoning.
They are neither customised nor finetuned, these models remain in their original form.
Power chatbots for general customer support
AI-powered solutions are transforming customer engagement and content creation. These group of models can assist with general customer support by acting as intelligent virtual assistants, capable of handling routine inquiries, guiding users through processes like account setup or troubleshooting, and providing instant answers to FAQs. They operate 24/7, reduce wait times, and seamlessly escalate complex issues to human agents, ensuring a smooth customer experience while lowering operational costs.
Support general summarisation and analysis
These are advanced language models that can be used in your enterprise environment to help process lengthy reports or research papers, extracting key insights and action points to accelerate decision-making.
Specialised MaaS
Provides an API key to models that are fine-tuned or trained for specific domains or custom requirements.
These models are optimized for industry-specific tasks or regional/local contexts, for example, a model that can predict, to a farmer, based on ambient conditions, the best crop to grow in a region.
This offering includes Cassava AI language models for African languages, enabling culturally and linguistically relevant AI solutions
Financial services models for fraud detection
Financial AI models can be incorporated into broader solutions that analyse transaction patterns, user behaviour, and historical data to identify anomalies in real time, reducing risk and safeguarding assets.
Healthcare models for medical text analysis.
Healthcare Models that process clinical notes, research papers, and patient records to extract critical insights, support diagnosis, and accelerate drug discovery, all while maintaining compliance with privacy regulations.
Localised LLMs for African languages in conversational AI.
Localised LLMs enable the building of AI solutions that capture culturally relevant and linguistically accurate interactions. This helps to bridge communication gaps and power inclusive digital experiences across diverse regions. These tailored solutions ensure businesses achieve higher accuracy, regulatory compliance, and user trust in mission-critical applications.
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