In the world of AI, things evolve at lightning speed. Every week brings new breakthroughs and headlines, and as we rush to keep up, time seems to slip away before we even notice a year has gone by.
As with our peers, we have been creating new value for you each day this year. Let's take a moment to look back at the highlights of this year.
To showcase our achievements in serving our clients, we have published 3 case studies this year:
We are offering the most cost-effective rate on these models.
| Platform | Price | Notes |
| Alibaba Cloud Model Studio (Singapore) | $0.03/image | Free quota: 50 images |
| Alibaba Cloud Model Studio (China) | $0.028671/image | |
| MuleRouter (Alibaba reseller) | $0.03/image | |
| fal.ai | $0.05/image | Est. by fal.ai |
| NetMind.AI | $0.026/image |
| Platform | Resolution | Price | Notes |
| Alibaba Cloud Model Studio (Singapore) | 480P | $0.05/second | Free quota: 50 seconds |
| 720P | $0.10/second | ||
| 1080P | $0.15/second | ||
| Alibaba Cloud Model Studio (China) | 480P | $0.043/second | |
| 720P | $0.086/second | ||
| 1080P | $0.143/second | ||
| MuleRouter (Alibaba reseller) | 480P | $0.05/second | |
| 720P | $0.10/second | ||
| 1080P | $0.15/second | ||
| Kie.ai | 720P | 12 credits/second (~$0.06) | Credit-based system |
| 1080P | 20 credits/second (~$0.10) | ||
| NetMind.AI | 480P | $0.04/second | |
| 720P | $0.08/second | ||
| 1080P | $0.12/second |
| Service | 2K Price | 4K Price |
| Kie.ai | $0.09 (18 credits) | $0.12 (18 credits) |
| Fal.ai | $0.08 – $0.15 | $0.20 – $0.24 |
| Nano Banana Pro (Google) | $0.14 | $0.24 |
| Leonardo.ai | $0.12 – $0.18 | ~$0.30 |
| Midjourney V6 | ~$0.20 (spread) | No native 4K |
| NetMind.AI | $0.12 | $0.20 |
We offer one of the fastest and most cost-effective DeepSeek APIs available!
We deliver best-matching performance with ParsePro at the lowest price on the market!
Let us help you turn your massive unstructured data into insightful structured data!
We have added 82 models into the model library this year!
In particular, we have also gone truly multimodal this year, added so many image, video, & audio models!
We launched our MCP hub this year, with over 300 useful MCPs at your service!
We have created the NetMind Application Hub, which is a collection of simple, ready-to-use tools designed for everyone. No technical setup, no coding required.
We have contributed our opinion to AI space throughout this year.
Great to have been trusted by these prestigious medias!
The important question for developers at the moment isn’t around how this technology substantively impacts the future of work, but how it can get there. Experts argue that the future of agentic AI is dependent on the improvement in reasoning ability. Kai Zou, founder and CEO of NetMind.AI, a data infrastructure company hosting a decentralized computing network providing rentable GPUs worldwide, sees the “coordination conundrum” of managing the actions of increasingly larger, more complex systems as one of the main hurdles to overcome. With this conundrum potentially leading to “inefficiencies, conflicts, and even system-wide failures if not properly managed,” Zou’s outlook on the future is that “ensuring that multiple autonomous agents work harmoniously towards a common goal, especially in dynamic environments, is a monumental task.”
"I look for a track record in finding product market fit, which reflects in healthy revenue in a suitably short window of time," says Seena Rejal, two-time AI founder, ex-venture partner at Fraser Finance, and deep tech investor across the US and UK.
Kai Zou, co-founder and CEO of NetMind.AI, explained it from another angle.“We talk about AGI as if it were a distant god,” he said, “but what we are really doing is refining the same old instinct, to automate thought the way we once automated labor.”And somewhere between the lines is also a critical distinction between myth and method.“People think AGI will arrive all at once, like a lightning strike. In truth, it is a slow accumulation of reasoning, context, and feedback loops. Every company that automates even a small cognitive task is adding a brick to that foundation.”Zou believes we are still years away from truly general intelligence, but that does not make today’s work less meaningful. “The path to AGI,” he said, “is being paved by people automating smaller decisions at massive scale. Every process that learns from its own outcomes is a step closer.”He paused, then smiled slightly. “The real question isn’t when AGI arrives. It’s whether we will be ready to use it wisely when it does.”Automation, he added, will not be a relic even when AGI arrives, instead, it’ll serve as the foundation. Examined from the perspective of the 1956 Dartmouth conference that gave the field its name, the goal of AI has always been to automate cognition the way the industrial revolution automated labor.“The day will come when systems can self-learn,” Zou said, “but even then, humans will still be in the loop setting direction and deciding what should never be automated.”He sees value in the blend itself, and dangers for those who look to AI for doing it all. “The danger is to treat AI as magic,” he said. “The opportunity is to treat it as a partnership.”That idea of partnership is where Shukla turns the conversation toward value. “Automation only works when it amplifies what humans already do well,” he said. “If it replaces thought instead of extending it, you’ve built expense, not value.”He paused, letting the thought land. “The question isn’t really how much AI can do,” Shukla continued. “It’s how much better people can perform because of it.”
"It marks a significant step forward in democratising AI and levelling the playing field with Big Tech," said Seena Rejal, chief commercial officer of British firm NetMind.AI, another early adopter of DeepSeek.
Seena Rejal, chief commercial officer of NetMind, a London-headquartered startup that offers access to DeepSeek’s AI models via a distributed GPU network, said he saw no reason not to believe DeepSeek.“Even if it’s off by a certain factor, it still is coming in as greatly efficient,” Rejal told CNBC in a phone interview earlier this week. “The logic of what they’ve explained is very sensible.”
Seena Rejal, chief commercial officer of AI startup NetMind, told CNBC the Chinese firm’s success shows that open-source AI is “no longer just a non commercial research initiative but a viable, scalable alternative to closed models” like OpenAI’s GPT.“DeepSeek R1 has demonstrated that open-source models can achieve state-of-the-art performance, rivaling proprietary models from OpenAI and others,” Rejal told CNBC. “This challenges the belief that only closed-source models can dominate innovation in this space.”
"OpenAI's restructuring shows that remaining independent is unattainable when operating frontier AI at scale. When you need $250 billion in cloud services, the relationship with your compute provider becomes structural rather than transactional. In a week where the Magnificent Seven will double down on AI as a growth strategy in earnings calls, this is a commanding step forward for Microsoft.""However, as Big Tech increasingly spreads its influence over those developing AGI, with Microsoft gaining access to all models until 2032, it raises questions about whether even more capital is being concentrated in the same few companies."
"Baidu's move to open source their LLM Ernie could prove more seismic than DeepSeek's January bombshell," Seena Rejal, chief commercial officer at AI infrastructure company NetMind, told AI Business."While DeepSeek was a proof of concept from a relatively unknown startup, Baidu brings institutional weight, capital firepower and crucially, the distribution channels to ensure widespread adoption. Despite U.S. chip restrictions, China remains capable of releasing high-performance AI models on the cheap. They're commoditizing the technology faster than the west can monetize it."
“A lot of what's being discussed at the moment lacks substance, definitely, and I think the reason is the whole thing is running way ahead of policymakers,” Dr. Seena Rejal, CCO of the AI startup NetMind, told me. “They can't really keep up with it because I don't think they really understand it at its core. So that is really quite dangerous.”
What will the future of AI accessibility look like when Big Tech no longer dominates the infrastructure? In this episode of Tech Talks Daily, I explore this question with Dr. Seena Rejal, the Chief Commercial Officer at NetMind.AI. Seena brings over 15 years of experience in deep tech ventures across the US and UK. As a two-time founder, investor, and now CCO of NetMind.AI, his mission is clear: democratize access to AI by breaking the centralized control of high-performance computing.NetMind.AI is pioneering a decentralized GPU computing platform through its blockchain-enabled NetMind Power, making AI affordable and accessible for everyone. But how exactly does decentralization level the playing field in an AI landscape dominated by major players? Seena shares his insights on how this approach not only empowers startups and researchers but also tackles some of the industry's most pressing challenges, such as GPU shortages, environmental costs, and Big Tech's increasing appetite for nuclear energy.
Integration remains the bottleneck. Seena Rejal, CCO at NetMind, an Enterprise AI provider, stresses, “Without an MCP, you could be spending time providing context to the LLM: explaining background and attaching relevant sources of information. With an MCP, you slash that time and get straight into asking your question and getting the job done. When you look at it this way, MCPs could provide a more straightforward route to unlocking the AI’s ROI through the productivity gains made.
One thousand days in, the biggest tangible benefit of generative A.I. for humanity is probably ‘democratization of empowerment.’ It has amplified our capabilities, giving us ‘superpowers’ in some areas, if you will. What’s incredible is how quickly all of this has become ubiquitous and almost the accepted new standard for how things get done: productivity in knowledge work, education and accessibility, healthcare advancements, operational efficiency and performance, creative expression. But we must also touch on the other side of this double-edged sword: deskilling and job hollowing, job displacement, bias and ethical risks, yearning for the human touch, misinformation risk, and concentration of power. A.I. is democratizing capability, but the keys to the kingdom are still held by a handful of players.
Xiangpeng Wan, product lead at NetMind.AI., described MCP as the "USB-C of LLMs ," recounting its rapid adoption by the major AI technology providers. "In March 2025 OpenAI announced it would integrate MCP into the ChatGPT desktop app and its Agents SDK," he said. "Then in April, it was Google DeepMind saying its Gemini models would support MCP as well. Microsoft and others not only back the protocol but have also released servers like Playwright-MCP so AI assistants can automate web actions through a browser." All of which points to MCP's emergence as the standard for connecting LLMS to external data.
According to Xiangpeng Wan, product lead at NetMind.AI, if a specific system doesn't have a server yet, a company can easily hire a third party or build one in-house. Since MCP is an open standard, anyone can make a compatible server, which, of course, also leaves room for paid, commercial options. Software vendors, he said, may ship official MCP connectors for their products and offer enterprise support. "That's one way to 'buy' an MCP integration. As for MCP as a Service, it's starting to appear, but it's still relatively early in the market, Wan said. Earlier this year, Cloudflare and others rolled out hosted MCP server options, so developers can deploy to the cloud with one click and let end users grant access via OAuth2. "This turns MCP into a managed platform and reduces the ops burden," he explained.
NetMind's Chief Commercial Officer Seena Rejal is also skeptical, saying that most productivity claims remain projections rather than proven outcomes. It's still early days, he said.
NetMind.AI, an artificial general intelligence research lab and infrastructure start-up uses AI-generated code widely, but directs senior engineers to design and maintain the critical foundation, covering identity, permissions, secret management and API contracts. The company then uses these as paved-path libraries and templates, and its AI systems generate demo and application logic on top of this framework, rather than from scratch. Xiangpeng Wan, the company’s product lead and strategic research lead, says he uses AI-generated code in all his projects now, but notes that humans must remain in the loop to review output and developers should maintain a “healthy dose of pragmatic scepticism.” Wan explains: “Before any code is committed, I routinely ask what edge cases may have been missed, whether the logic makes business sense and, most importantly, whether I fully understand what the code is doing.”
"I think there are two valid substitutes for MCP," said Xiangpeng Wan, product lead at NetMind.AI. "One is called the Universal Tool Calling Protocol (UTCP), which allows direct API calls, no server overhead, low latency, and leverages existing tool security features. The other is called Agent-to-Agent Protocol (A2A), which focuses on agent collaboration rather than tool access, and is backed heavily by Google and Microsoft." Wan said UTCP has good odds for replacing MCP, A2A has the best odds, and function calling (the AI capability to access and execute external tools or APIs) has the least chance. That said, he added that he doesn't see a single protocol dominating soon. "What we'll most likely see is a combined ecosystem of MCP, UTCP, A2A, function calling and managed solutions in the near future," Wan said.
“The premium on closed AI models will collapse in 2026. Airbnb’s CEO already proved this when they shifted massive workloads to open-source models like Qwen to cut costs. The gap between expensive closed models and free open ones has essentially disappeared. We’ve hit a physical wall in reasoning capabilities.“Companies will also no longer be willing to let their core data sit in black-box clouds anymore. Data sovereignty means businesses are moving AI back to their own infrastructure.“Meanwhile, the bottleneck in the AI arms race is shifting from silicon to electricity. Data centres have the GPUs but can’t plug them in. Power grids can’t keep pace with training, reasoning and inference demands. Microsoft’s future isn’t constrained by NVIDIA anymore; it’s constrained by nuclear plants and substations.“In the workplace, job adverts for junior roles will diminish. Companies won’t hire and train expensive newcomers when one architect can manage AI agents. Any job without high-level judgment or genuine human connection is getting automated to save money.”
We have also been writing AI insights ourselves for you. And we have published 22 articles this year!
And how can we not share these great insights into the communities on Reddit, as they would reward us with upvotes! We have gained over 10k upvotes in 2025, since we started running Reddit in August.
You know what's better?
We are the top 1% poster in r/Qwen!
We are also in the top 5% poster in r/ChatGPT, r/DeepSeek, r/AgentsofAI, r/learningmachinelearning & r/LLMDevs.
In case you missed it, here's our top posts:
AI may already pose more harm than good in the e-commerce sector in r/ChatGPT (382 Upvotes)
DeepSeek Just Beat GPT5 in Crypto Trading in r/DeepSeek (248 Upvotes)
Found an Opensource Goldmine in r/LLMDevs (185 Upvotes)
LinkedIn now tells you when you're looking at an AI-generated image, if you haven't noticed. in r/ChatGPT (155 Upvotes)
Also sharing on LinkedIn, also rewarded.
We have had significant follower growth by over 4000 in 2025, reaching 10000 followers in Oct.
At NetMind, our core mission is to make AI accessible to everyone. That is why we offer unbeatable pricing on our model APIs and MCPs, along with free AI tools and enterprise-grade solutions.
Now we are taking a major step forward with NetMind XYZ, a platform designed to help small business owners (even a one-person laundry shop) harness the power of AI agents for marketing, sales, customer service, and more.