Arcee AI Review: Features, Integrations, and Pricing 2024

Arcee AI is a small language model training, adaptation, and deployment system. As we’ll discuss later, a Large Language Model (LLM) performs human-like tasks using its vast data sets. Despite its many advantages, it might not be the best choice for specific use cases. 

This is where Arcee AI comes in. Instead of an LLM, it focuses on building small language models (SLMs) for more specialized use cases. It creates your SLM based on smaller data sets, including your enterprise’s. This article reviews Arcee AI, its features, integrations, and who can benefit from it.

Arcee AI Overview 

Arcee AI builds context-adapted and domain-specific LLMs through its domain-adapted language model system (DALM). However, to understand what Arcee does, you must first understand SLMs and LLMs. Small Language Models (SLMs) and large language models (LLMs) are distinct approaches to artificial intelligence, each with unique advantages and capabilities.

LLMs, such as GPT-4 and Llama 2, boast billions or even trillions of parameters, showcasing impressive capabilities in language processing. However, their extensive size has challenges like high computational power requirements, storage needs, and limited accessibility. SLMs operate on a more modest scale. Its parameters range from thousands to a few million. They are also more accessible and feasible for organizations that may lack the resources to manage the computational load demanded by larger models.

Arcee AI helps enterprises build, train, and deploy their SLMs. Its SLMs provide control and tailoring, allowing enterprises to fine-tune models for specific domains and tasks. Since SLMs consume less energy and operate on hardware with lower specifications, these organizations can deploy them in resource-constrained environments.

Furthermore, Arcee AI’s powerful adaptation system enables various tasks that require the understanding of natural language. It also allows rapid training and inference, streamlining workflows through its Virtual Private Cloud (VPC). All these, plus accurate insights, make it valuable for timely decision-making.

Jacob Solawetz, Mark McQuade, and Brian Benedict launched Arcee AI in February 2023. Its investors are Long Journey Ventures, Flybridge, Centre Street Partners, Wndrco, 35V, AIN Ventures, and Hugging Face CEO Clément Delangue. 

Although the company is only a year old, it has received 5.5 million in venture funding. We attribute this partly to the founders’ experience. The trio had previously worked with tech startups, some in engineering and some in business development.

• Established: 2023
• Founders: Jacob Solawetz, Mark McQuade, and Brian Benedict
• Office: Miami, Florida, United States. 

5 Core Features of Arcee AI

Expert Opinion

• User experience (Integrations)– 1/1
• Features quality– 1/1
• Customer service– 0.8/1
• Security– 0.7/1
• Pricing – 0.8/1

Rating: 4.3/5

Arcee AI helps enterprises develop context-adapted large learning models for deployment in more specific environments.

Arcee is a pioneering platform that aims to transform how enterprises leverage generative AI (GenAI) technologies. It also addresses critical issues around data security and model transparency that many businesses face today.

At first, we were attracted to its move against the current trend. At a time like this, where gen AI companies compete to create better LLMs, we were surprised to see Arcee focus on SLMs. While we thought receiving attention in the industry might take a while, Arcee closed its seed funding round.

Although we love its initial value proposition, we find its integration with Mergekit even better. Enterprises with limited resources can implement open-source models with their SLMs. It also provides a virtual private cloud (VPC) that facilitates the deployment of specialized GenAI models within secure, private cloud environments. This is especially useful for industries like legal, healthcare, insurance, and financial services, which are heavily regulated and possess highly proprietary data.

Arcee distinguishes itself by offering an end-to-end, adaptive system for training, deploying, and monitoring GenAI models. This is impressive as it ensures superior fine-tuning capabilities and enhanced security to mitigate privacy risks. The platform’s ability to operate within a virtual private cloud provides businesses with the assurance of data privacy and full ownership of their AI models and technology stack.

Arcee’s focus on addressing the specific needs of highly regulated industries and its commitment to security and privacy positions it uniquely in today’s GenAI market.

Notable Features 

Arcee AI’s platform boasts several features that give enterprises full ownership of their AI models. It provides secure, end-to-end generative AI systems for highly regulated industries. Some of these features are:

1. SLM Adaptation System

SLM adaptation system is the process of customizing and fine-tuning Small Language Models (SLMs) to suit specific applications, domains, or tasks. They offer a compact and efficient solution for natural language processing (NLP) tasks. However, organizations can enhance their effectiveness by adapting them to the unique requirements of a particular use case.

Arcee provides a domain-adapted language for you in the following steps. First, it identifies the specific domain or task for which you’re building the SLM. This could range from healthcare and finance to customer service or legal documentation. Next, it gathers and preprocesses domain-specific data. This includes text corpora, documents, or user interactions relevant to the target domain.

After collection, it fine-tunes the pre-trained SLM by carrying out domain-specific training. This is the retraining of an SLM using domain-specific data to adapt its language understanding capabilities. It may also add domain-specific features or constraints to the training process to improve model accuracy and relevance.

2. Virtual Private Cloud

Arcee’s virtual private cloud (VPC) helps businesses train and deploy their SLM in a secure environment. A Virtual Private Cloud (VPC) is a safe and isolated portion of a public cloud infrastructure. It could be Amazon Web Services (AWS) or Google Cloud Platform (GCP). It is also logically segmented to mimic the capabilities of a traditional private network. It’s like having your own private space within a shared cloud environment.

In a VPC, you can define your virtual network topology, including IP addresses, subnets, routing tables, and network gateways. Additionally, VPCs offer the flexibility to connect securely to on-premises infrastructure or other cloud environments using VPN (Virtual Private Network) or dedicated connections.

With Arcee’s VPC, your SLM training, deployment, and maintenance happen in one place. This results in scalability and resource optimization, as you can scale up or down as you wish.

3. SLM Maintenance and Upscaling 

Even after the adaptation and deployment, you may need to adjust model parameters, such as learning rates or model architecture, to optimize performance for the target domain. Arcee ensures that you can constantly improve your SLM to maintain quality.

You can then deploy the re-adapted SLM in production environments to perform various NLP tasks with enhanced accuracy and effectiveness. It could be text generation, sentiment analysis, or language translation.

Furthermore, constant maintenance can help you maximize opportunities for innovation and differentiation. It will also help you implement updates that drive value and impact in your industry.

Arcee AI Use Cases

You can use Arcee AI to build context-adapted LLMs for various industries. Some of these industries are:

i. Legal

The legal sector demands efficient and accurate solutions. Arcee’s specialized Small Language Models (SLMs) can address various legal challenges. One significant application is regulatory compliance. Here, Arcee’s SLM Adaptation System monitors and ensures adherence to laws and regulations. This minimizes the risk of non-compliance and associated penalties. By maintaining a solid reputation in the market, legal teams can confidently navigate complex regulatory situations.

Another critical use case is due diligence automation. With Arcee, you can build AI applications that enable the identification of critical issues and risks in transactions. This process enhances time and cost efficiency while ensuring thorough review and accuracy. Additionally, Arcee facilitates E-Discovery creation for sifting through vast amounts of electronic data, providing comprehensive case preparation.

ii. Healthcare

Arcee’s Small Language Model (SLM) adaptation system can help build healthcare solutions for patient care and administration. Its Domain-Adapted Language Model (DALM) simplifies medical coding and billing while reducing errors. Your healthcare AI can match individuals with suitable clinical trials by analyzing patient data. Additionally, you can use it for treatment planning by suggesting personalized care plans and treatment efficacy methods.

With Arcee, you can also build solutions for automating patient communication and providing round-the-clock support. Furthermore, it can aid in diagnosis by analyzing symptoms and medical research, suggesting potential diagnoses for evaluation.

iii. Finance

By leveraging Arcee’s end-to-end SLM adaptation system, finance teams, and companies can build specialized models to streamline operations. One critical application is transaction processing automation. Your SLMs categorize and process financial transactions, reducing human errors and improving speed. They can also detect fraud by analyzing transaction data, enhancing security and compliance with regulations while minimizing financial losses.

With Arcee, enterprises can develop AI analytics tools for portfolio management. It can work as an investment support and trend prediction. Furthermore, SLMs aid in risk assessment by assessing credit, market, and operational risks.

Arcee Integrations

Arcee announced its integration with a few AI-building solutions this year. One of them is Mergekit, which supports merging several language models. The other is Langchain, which helps you build AI applications with chains. Here’s a brief overview of both:

1. Mergekit Integration

Mergekit and Arcee’s collaboration is among the most interesting in language model development. Users can utilize sophisticated open-source models through Mergekit’s model merging capabilities integrated into the Arcee platform. Apart from being cost-effective, you can also tailor it to specific domains.

With Mergekit’s out-of-core approach, even resource-constrained environments can efficiently execute complex merges. Mergekit’s founder, Charles Goddard, has joined the Arcee AI team as part of the consolidation. His expertise, combined with Arcee’s team, will only mean continuous enhancement of Arcee’s capabilities.

Mergekit is part of Arcee’s SLM adaptation system. In other words, it’s one of the features you access while building your AI. 

2. LangChain Integration

Arcee’s collaboration with Langchain offers enhanced flexibility in building domain-specific AI models. Users can create a wide range of AI applications by combining Arcee’s generators and retrievers with Langchain. An example is retrievers to fully autonomous systems. To set up Arcee and Langchain, you have to install the necessary packages and sign up for an account. You can then train your Domain Adaptive Language Models (DALMs) using Arcee’s platform or APIs.

Arcee also provides advanced configurations for generation and retrieval, allowing users to tailor output according to specific needs. This integration allows you to develop contextual chatbots, semantic search engines, and knowledge bases.

Plans and Pricing

The SLM building software does not include pricing information on its website. Its pricing follows a custom model. In other words, the cost varies based on several factors, including the size of the dataset for training, the language model, industry, etc. Therefore, interested organizations have to reach out to the company first. To do this, click the “Book a Demo” button and follow the instructions on the page. 

You must fill out a form on the page asking for your name, company name, and work email. You may also need to answer a few questions, such as the cloud provider your company uses, the specific use case your SLM is for, and your progress in building AI models. Note that the company offers a virtual private cloud for deployment. However, it can also work with your existing VPC.

Customer Support

Before employing Arcee AI for your SLM development, booking a demo is the only way to reach its representatives. To do that, follow the steps in the pricing section above. Other means through which the company offers customer support are its resources. You’ll find insights, news, product updates, and more there.

Also, check out the blog for updates and developments. Furthermore, Arcee AI’s founders are very active on social media. You can catch them sharing updates about the software on LinkedIn or Twitter. Consequently, you can follow them on their pages, ask questions when necessary, or express concerns. 

Conclusion

Arcee AI offers a comprehensive solution for building, training, and deploying Small Language Models (SLMs) tailored to specific applications or domains. By leveraging its SLM adaptation system, businesses can fine-tune models for enhanced accuracy and effectiveness in natural language processing tasks. 

The platform’s Virtual Private Cloud (VPC) ensures secure training and deployment, while features like maintenance and upscaling enable continuous improvement and innovation. Despite being relatively new, Arcee AI is receiving attention for providing end-to-end generative AI systems for highly regulated industries. Its custom pricing model and robust customer support options make it a valuable resource for organizations leveraging AI. Visit its website to get started.