Decidr

Integrating AI into your business is quickly moving from a luxury to a necessity as the landscape becomes increasingly competitive. It allows businesses to achieve more with fewer resources, freeing up employees to focus on more strategic and creative tasks.

While the potential benefits of AI are immense, the perception that it requires a significant financial investment can be daunting for many SMEs. And with good reason, because it usually does – especially when it comes to custom AI models and integrations that go beyond off-the-shelf solutions.

However, implementing AI doesn't have to be prohibitively expensive.

Platforms like Decidr are revolutionising how businesses of the future will operate by integrating business data to train specialised AI micro-roles, allowing them to achieve high impact without the need for large budgets.

The AI cost barrier for SMEs

Despite the increasing benefits of implementing AI, small businesses face numerous challenges in doing this.

One of the biggest roadblocks is of course the cost. Implementing AI technologies can involves the price of hardware, software and specialised personnel.

The investment can even be substantial just to access services — often subscription based — from major providers.

For instance, Google offers a range of services through Vertex AI — its dedicated machine learning platform for prototyping and testing generative AI models.

Vertex AI agents will set you back US$12,000 per 1,000 queries and $0.002 per second for Vertex AI Agents Voice. And this is just the tip of the pricing iceberg.

Additionally, Google Gemini for Workspace (formally Duet AI) starts at US$28 per user per month for the Business plan, or US$42 per user per month for Enterprise.

And just last month at Google I/O, the tech giant showed off its updated 1.5 Pro and Gemini 1.5 Flash models, which are available globally now.

According to Google, Gemini 1.5 Pro costs US$7 for one million tokens and prompts, with prompts up to 128k coming in at US$3.50 per 1 million tokens. For Gemini 1.5 Flash, pricing starts at US$0.35 for 1 million tokens.

Then there’s SaaS tycoon Salesforce which offers its Einstein GPT for Sales at US$50 per user per month. The same goes for its Service Cloud Einstein pricing.

Meanwhile, its Einstein 1 Sales subscription costs $700 per user per month.

These are just a few small examples, but they demonstrate how quickly the costs can add up, making it difficult for smaller businesses to justify the investment.

While these prices reflect the advanced capabilities and comprehensive support provided by these platforms, they also highlight the financial barriers that many SMEs face when considering AI adoption.

Additionally, ongoing costs for cloud usage, support, maintenance and enhancements can sell for thousands per month alone.

And let’s not forget that some of these are cookie cutter offerings. If a company wants its own custom model, it often needs to have very deep pockets.

As OpenAI said last year, customers who want a custom model trained on GPT-4 will have to shell out between US$2-3 million and also wait several months for delivery.

The knowledge gap

Other integration issues arise when it comes to retrofitting into an existing system.

Small businesses often rely on legacy systems that may not be compatible with modern AI technologies. Integration can be complicated and time consuming, requiring significant changes to existing infrastructure.

The problem with this approach is the failure to recognise that AI isn’t just another SaaS product. It’s its own category and needs to be treated as such.

Then there’s the matter of managing and securing sensitive data. SMEs may struggle with data privacy laws, ensuring robust security measures and maintaining high quality data for AI training.

Small businesses often lack the in-house expertise needed to implement and manage AI systems effectively.

AI is a specialised field requiring deep knowledge in data science, machine learning and technical development.

Small businesses often need to rely on external consultants or vendors for AI implementation. This can be costly and may not always align with the business's specific needs.

It’s no wonder then that while there's a great deal of interest in AI from SMEs, current adoption rates are a little murky.

A report from Xero in 2023 found that 32% of small businesses in Australia, Canada, New Zealand, Singapore, the UK and US weren’t taking any proactive steps to adopt AI.

The number is higher when looking at the general business landscape, with PwC’s 2024 AI Business Predictions report finding that over 54% of businesses have already embraced generative AI.

Clearly, barriers such as time, infrastructure and knowledge hinder the ability of small businesses in particular to implement AI solutions. And so does the cost.

The Decidr solution

Decidr addresses these challenges by providing an accessible and user-friendly platform that simplifies AI integration. This enables SMEs to overcome these barriers and leverage AI to enhance their operations and competitiveness.

By leveraging Decidr’s expertise, businesses can avoid the high costs and complexities associated with building an in-house AI team.

How we help you achieve scale and impact

Decidr is at the forefront of this AI revolution, providing a network of specialised AI micro-roles that handle most digital tasks. And this is important, because businesses have thousands of workflows, each with multiple tasks that need addressing.

But one of the key advantages of Decidr’s AI solutions is our ability to achieve high impact without the need for complex integrations into old Saas systems.

Decidr’s micro-agents operate with all business data, providing a seamless and efficient solution for businesses looking to scale.

Decidr’s unique approach involves using both structured and unstructured prompt inputs to create common workflows.

Custom AI business constitutions are mapped with conditional logic-enabled models, resulting in thousands of specialised agents for every part of every workflow. This unique approach involves using both structured and unstructured prompt inputs to create common workflows.

But what does this look like in practice?

Imagine an integrated network of AI agents that support the entire sales pipeline – data entry, updating, outbounding and contract production. Not only will this save you admin time, it also speeds up the revenue process.

What about being able to offer your customers 24/7 report from AI agents that aren’t just aware of all of their tickets and company policies, but also historic outcome of similar tickets in order to make the best and most informed choices?

How about the ability to offer perfect memory of all detailed transactions and applying these to your financial goals, recommending the best approach based on hard data?

This networked, goal-based, multi-agent approach ensures that businesses can achieve their objectives without the high costs typically associated with AI deployment.

Something so comprehensive may seem like it would require overwhelming onboarding – not with Decidr.

By ingesting diverse data types, Decidr’s architecture allows for rapid onboarding in just 20 minutes, ensuring that businesses can quickly benefit from AI integration.

Decidr’s solutions are also designed to be affordable, making them accessible to businesses of all sizes.

For example, while AI solutions can cost anywhere between US$5,000 and US$300,000 (or more for custom AI models), Decidr ensures that businesses can achieve similar benefits at a fraction of the cost.

By enabling businesses to scale operations without the need for large budgets, Decidr is helping SMEs to be able to adopt AI, modernise their operations and secure their futures in a market that has no intention of slowing down.