Aguru LLM Router vs NewOaks: Which is better?

Aguru offers a robust LLM Router integrated with advanced features like LLM Caching, and Data Clustering & Visualization. It is designed to optimize your LLM usage by balancing quality and cost, reducing response times, and providing meaningful insights into your data. Our LLM Router allows you to select from over 100 available LLM models for your AI application, and dynamically routes each prompt to the best-suited model based on an optimal quality-cost balance. Our LLM Caching solution reuses past responses for new, similar prompts, significantly reducing LLM usage and enhancing response times. Additionally, our Data Clustering feature transforms unstructured data into semantic clusters, each representing a distinct use case. It also provides performance scores across various LLM models for each cluster, enabling you to make informed decisions on the most appropriate LLM models for your specific use cases.

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NewOaks

- NewOaks is a platform that uses AI to improve business management processes and automate tasks. - It offers analytics tools that help optimize resources, make informed decisions, and improve overall efficiency, helping companies grow and evolve.

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Key features

Aguru LLM Router

Embedded Integration: Aguru seamlessly integrates into existing platforms without disrupting current workflows.
Monetization of Outcomes: Focuses on monetizing completed work rather than just features, allowing SaaS companies to generate new revenue streams.
High-Trust Workflow Management: Designed for complex workflows that require reliability, auditability, and stakeholder coordination.
Durable Execution Engine: Includes built-in checkpoints, retries, and automated recovery to handle errors and ensure consistent task completion.
Stakeholder Coordination: Manages communication across various channels, addressing non-responses and exceptions to keep workflows moving efficiently.

NewOaksNo data

Useful for

Aguru LLM Router

Aguru LLM Router vs NewOaks: Which is better?

Aguru LLM Router

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NewOaks

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Key features

Aguru LLM Router

Embedded Integration: Aguru seamlessly integrates into existing platforms without disrupting current workflows.
Monetization of Outcomes: Focuses on monetizing completed work rather than just features, allowing SaaS companies to generate new revenue streams.
High-Trust Workflow Management: Designed for complex workflows that require reliability, auditability, and stakeholder coordination.
Durable Execution Engine: Includes built-in checkpoints, retries, and automated recovery to handle errors and ensure consistent task completion.
Stakeholder Coordination: Manages communication across various channels, addressing non-responses and exceptions to keep workflows moving efficiently.

NewOaksNo data

Useful for

Aguru LLM Router

Use cases

Aguru LLM Router

Safety Certificate Renewal: Automates the end-to-end process of renewing gas safety certificates for tenanted properties, coordinating multiple stakeholders and ensuring compliance.
Supplier Delay Recovery: Monitors supplier performance and manages communication to recover from delays in manufacturing processes, preventing production disruptions.
Order Fulfillment Exception Handling: Addresses and resolves exceptions in order fulfillment by investigating stock and order statuses, coordinating necessary actions to ensure timely delivery.
Purchase Order Confirmation: Automates the confirmation process for purchase orders, including follow-ups with suppliers and updates on order details, ensuring accuracy and accountability.
AP Invoice Exception Handling: Streamlines the approval process for supplier invoices by checking for discrepancies, gathering necessary documentation, and managing vendor communications.

NewOaksNo data

Price

Aguru LLM Router

Aguru operates on a usage-based pricing model, where customers pay for completed workflows.
There are no upfront software fees; costs are incurred only when value is delivered.
The pricing includes an ISV revenue share from execution fees for each completed workflow.
The initial mapping stage takes 2-4 weeks, followed by a pilot build that typically takes 4-8 weeks to go live.
For larger deployments, Aguru can support deeper integrations and higher execution volumes with a predictable platform fee.

NewOaksFree