Artificial Intelligence
This past January, the tech world was turned upside down: A new AI model that matched the performance of OpenAI’s o1 model at a fraction of the cost caught the world’s attention.
DeepSeek took the tech world by storm not only because of its R1 model’s ability to reason, learn from other models and “think,” but also because it shows the potential for innovative AI companies in addition to tech giants — Microsoft, Google, OpenAI, etc. — to emerge as a force to be reckoned with in tech.
Beyond foundation models: How AI players outside of tech titans are ushering in AI innovation
The buzz surrounding DeepSeek in accelerating AI innovation has left many wondering how an AI startup, and not an existing tech giant, was able to achieve such a feat. But in the broader AI ecosystem, these AI companies are where innovation has always happened.
Most discussions surrounding AI, gen AI and now, agentic AI focus on well-known foundation models, like ChatGPT or Gemini, and their providers, including OpenAI, Google and Meta. In fact, according to a recent Prosper Insights & Analytics survey, 29.3% of U.S. adults have heard of gen AI, like ChatGPT, and use it.
Prosper – Heard of Genetrative AI
However, the broader AI ecosystem, which includes AI cloud platforms, independent software vendors, integration technologies and system integrators, is also leading the charge in bringing AI-driven economic value to enterprises and consumers.
For instance, Tredence is a services provider that implements AI and data engineering solutions for large enterprises, providing system integration in the AI ecosystem. System integration ensures AI-powered applications work within enterprise environments. As a system integrator, Tredence uses foundation models to build applications, improving their performance in specialized areas for enterprises, such as supply chain management or customer analytics. As a result, system integration is where a lot of innovation is happening with startups and other companies besides tech giants.
“Companies outside of the Microsofts and the Googles of the world are also ushering in the next wave of AI innovation, seeing where the gaps are as customers and enterprises start adopting AI,” said Unmesh Kulkarni, SVP Gen AI at Tredence. “Because of this, we’re able to find niche spots where tech giants aren’t present yet. This is how innovative AI companies can differentiate themselves and stand amongst the giants.”
The power of prioritizing speed and agility
One way AI companies can differentiate themselves is through their speed and agility.
Speed matters, especially as the gen AI landscape continues to evolve. That means it’s up to AI companies to move as fast as gen AI evolves in order to deliver business value and deploy AI solutions.
Agile and innovative AI companies can rapidly adopt and implement new technologies and generate business value from them. For example, Tredence invested 10% to 15% of its resources into accelerating its team’s AI and gen AI skills, which is critical as more enterprises adopt the technology. According to McKinsey research, 71% of respondents say their organizations regularly use gen AI in at least one business function, up from 65% in early 2024.
As a result, Tredence developed an AI Center of Excellence to focus on understanding AI technology trends faster and converting them into real value. This allowed its team to hone in on applied research work being done on AI and back into developing assets and accelerators for customers, helping them implement AI in half the time. Tredence, in comparison to a tech giant, can move faster, deploy AI solutions, and focus on AI to deliver better results and keep up with technological changes.
“Speed and agility are major opportunities for AI companies that they must take advantage of,” said Kulkarni. “Our size allows us to dedicate a portion of our company to solely focus on gen AI, which was an intentional decision. This enables us to quickly roll out new AI solutions and AI initiatives at scale because we are focused.”
Going all-in on agentic AI
Another area of opportunity for innovative and agile companies is heavily focusing on gen AI and now, agentic AI — the next evolution of intelligent systems that can reason, prioritize, and act across enterprise workflows.
By making deep investments in agentic AI, companies can position themselves ahead of the curve as enterprises begin to shift from simple automation to autonomous workflows powered by intelligent agents — 25% of companies that use gen AI will launch agentic AI pilots or proofs of concept, growing to 50% in 2027, according to Deloitte.
For example, Manus AI is a startup that’s making waves in the tech world by heavily investing in agentic AI. By building agents that can reason, prioritize, and make decisions across entire business workflows, Manus AI prioritizes solving actual business problems through AI that thinks, reasons, and delivers — a needed innovation since 24% of users use gen AI as a personal assistant, according to a recent Prosper Insights & Analytics survey. Because of this, Manus AI is ushering in work automation where users don’t have to monitor everything an agent does, as opposed to tech powerhouse AI models like ChatGPT or Claude.
Prosper – Use Generative Artifical Intelligence For
Similarly, Tredence understands that the next frontier of gen AI is autonomous execution, especially for enterprises. As a result, Tredence is channeling resources into understanding how these technologies evolve and translating that knowledge into real-world impact for enterprises.
Solving complex enterprise AI challenges at scale
Finally, solving complex enterprise AI challenges is another way for agile and innovative companies to make their mark in AI.
With more enterprises evolving towards autonomy with increasingly advanced reasoning and logic capabilities, it requires them to move beyond prompt engineering and retrieval-augmented generation. To do so, they’ll need to identify their top use cases, map them to relevant agents and design a comprehensive platform (that is multi-cloud, multi-LLM) with strong governance for deploying these solutions. This is an opportunity for innovative and agile AI companies to fill this gap and assist enterprises in solving this complex challenge.
For instance, one of the largest food companies with over $50 billion in revenue wanted to optimize its marketing budget allocation for an upcoming campaign across social, digital, and in-store channels. By deploying multiple agents, Tredence was able to autonomously analyze market data, optimize budget allocation, evaluate channel performance, and suggest creative content, transforming the confectionery company’s complex marketing decisions into actionable data-driven strategies.
“As enterprises evolve toward AI-driven autonomy, they need more than just prompt engineering — they need intelligent agents that can reason, act and adapt at scale. This is where agile and innovative AI companies like Tredence must step in and stand out among tech giants,” said Kulkarni.
The AI ecosystem has multiple components beyond large AI giants, and they work together. By prioritizing speed, going all-in with agentic AI, and solving complex enterprise problems at scale, AI companies, in addition to tech titans, will be well-positioned to accelerate innovation and reshape the AI landscape for years to come.
