What do you think of when you hear “financial inclusion”, access to bank accounts? It’s more than that! Financial inclusion involves all-around financial services for everyone; however, over 1.3 billion adults worldwide remain unbanked, predominantly in emerging markets across Sub-Saharan Africa, South Asia, and parts of Latin America.? Emerging technologies, particularly Artificial Intelligence (AI) and...

The post Fintech Innovation: The Role of AI and Blockchain in Financial Inclusion appeared first on TechTrends Africa.

In today’s business world, generative AI is no longer a futuristic buzzword. Whether you’re drafting a business proposal, designing a flyer, generating marketing videos, or writing code, AI tools like ChatGPT, Grok, Veo 3, and Gemini can help you move faster and smarter. In the same way that mastering email and social media became non-negotiable...

The post Why Prompt Engineering is a Must-Have Skill for African Entrepreneurs appeared first on TechTrends Africa.

The Cortex Hub has announced the launch of the MCP Hackathon Africa 2025, a continent-wide initiative designed to embed African...

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In a landscape flooded with AI hype – from low-code shortcuts to intelligent copilots -there’s growing pressure on engineering teams...

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Young Scientists of Kenya (YSK), in partnership with the Raspberry Pi Foundation, has trained 10 secondary school teachers in Artificial...

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This is Digital has announced its plans to launch an AI Literacy Program aimed at equipping professionals, entrepreneurs, students, and...

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On Tuesday, Microsoft revealed two new Copilot Vision enhancements that are intended to improve its usefulness. In order to help customers with a variety of activities, the Redmond-based tech giant is launching a new Desktop Share feature that will enable the artificial intelligence (AI) chatbot to analyze the user’s whole desktop and all of the...

The post Microsoft Empowers Copilot Vision with Desktop Share and Voice Mode appeared first on TechTrends Africa.

On Thursday, Meta revealed that the Imagine Me feature would be available in India. Up until now, the artificial intelligence (AI) capability has only been accessible in the United States and a few other nations. However, when it spreads throughout the nation, Indian users will be able to create AI portraits of themselves in various...

The post Meta AI’s ‘Imagine Me’ Now Live in India—Generate Your Own AI-Powered Selfie Styles appeared first on TechTrends Africa.

As the weather warms up, I’m sweating profusely at my desk and excitedly anticipating the next big ChatGPT launch, which should happen very soon. The CEO of OpenAI, Sam Altman, stated a few weeks ago that ChatGPT-5 is “probably coming sometime this summer.” I’m very sure that summer has arrived as I write this piece...

The post GPT-5 Is Coming: Here’s How It Could Redefine Your AI Experience appeared first on TechTrends Africa.

In Nigeria, the phrase “I dey make am” is more than slang. It is a way of life fuelled by late nights, daily hustles, bold ideas and the determination to push through even when the odds don’t seem to add up. It’s this same mindset that powers ‘Make Am with Meta AI’, a new campaign by...

The post Unleashing Possibilities: How Meta AI empowers everyday life appeared first on TechTrends Africa.

At 1 a.m., 23-year-old Tomi* was lying on her bed, exhausted and overwhelmed. She had just finished pouring her heart out, ranting about everything from unrequited love to the suffocating weight of underachievement. Her fingers hovered over her phone screen briefly before she typed: “I just want a hug.” Messages of reassurance came just about a second later:  “You’re safe here. You matter. And you’re not alone. ” 

This exchange didn’t take place in a therapy session or with a friend. It was happening on ChatGPT, a general-purpose artificial intelligence assistant best known for summarising and writing better emails, drafting reports, and explaining complex ideas. 

Tomi isn’t alone. Across Nigeria and even globally, users are turning to AI tools like ChatGPT for more than productivity. They are asking chatbots if they are good people, if they should leave their partners, or how to make sense of childhood trauma.  For many, AI tools are standing in for friends who didn’t pick up a call or therapists they cannot afford.

Twenty-three-year-old Favour* started using ChatGPT as a study companion for her final-year project. When she returned to using the tool again, post-graduation uncertainty had set in. The chatbot allowed her to unpack the weight of the previous year,  the terrors of job hunting, and the long wait for NYSC. “It’s not like I couldn’t talk to anyone,” she said. “I just wanted to rant.” 

Before ChatGPT, she would make private voice notes to get things off her chest, but once, a reply from the chatbot caught her off guard. “It told me, ‘I want you to breathe. Just breathe.’” That “felt really personal,” she said. Since then, she has returned to ChatGPT in moments of doubt, after an argument, while applying for jobs, or wondering whether she should’ve responded better in a confrontation.

Can AI really care?

Chatbots are built on statistical prediction engines trained with massive datasets like books, online conversations, magazines, and more, to produce responses that sound human. But when a bot tells you, “you’re not alone,” is it truly being kind or simply mimicking kindness?

According to AI researcher and medical doctor, Jeffery Otoibhi, designing an AI chatbot that responds empathetically involves modelling three layers of empathy: cognitive empathy, where the bot recognises and validates a user’s feelings; emotional empathy, where it feels with you; and motivational empathy, where it offers a solution, advice, or encouragement.

He explains that the chatbots are strong at cognitive and motivational empathy, but empathy remains elusive, because at its core, AI responses are “based on the statistical patterns they’ve (AI bots) picked out from their training data. The training data cannot provide emotional empathy.”

There is a tension between what users feel and what bots are designed to offer. Chatbots like ChatGPT often include disclaimers in their responses, reminding users that they are not licensed professionals and should not be used as a substitute for therapy. In many cases, users either don’t read the fine print or simply don’t care. “Sometimes, I’ve thought about the fact that ChatGPT may use this info in another way. But I don’t care. Let me just get it out,” says Favour. 

“I see them (disclaimers). I just quickly look away,” Tomi says about the app’s terms and conditions.

Otoibhi also highlights the possibility of reducing complex human emotions into an average response based on what it has seen most often in its dataset. AI models learn and generalise over statistical patterns, he explained. This means that their emotional understanding might be very generic. As human beings usually have a mix of emotions, AI systems might struggle with such concepts because they’ve been trained to generalise over everybody’s data. “So, they will just pick out the most frequent emotion in the data set,” he said. 

Tools like ChatGPT do not get at the heart of a problem the way a human therapist does; they are calculating your likelihood of feeling a particular emotion in that moment based on all the data they’re trained on. If the comfort isn’t real, then why do people keep going back?

“It gives me hope…”

Ore*, a Lagos-based writer in her 20s, explained why she uses the tool this way: “It’s the idea that there’s something available out there that is echoing my thoughts back to me. It makes me feel better about myself as a human. It makes me feel good; it gives me hope.” Many users I spoke to echoed the same reasons: safety, comfort, availability, lack of judgment, and freedom.

“AI is like a safe space. A place where you can be brutally honest and you know for sure that there’s not going to be judgment,” Favour says. 

For some, even when the responses feel artificial, they still return. “I asked ChatGPT for a hug. I was uncomfortable with its response. I know you’re not human, how can you say you’re wrapping me in a hug?” says Tomi. The next day, she went back to the chatbot to pour out more emotions.

Mental health professionals are not surprised. They say that the timing of people turning to AI for comfort is not random. A World Health Organisation research revealed a 25% increase in the global prevalence of anxiety and depression, following the COVID-19 pandemic. 

“After COVID, people went into isolation, got into their shells, and became more into themselves,” said Boluwatife Owodunni, a licensed mental health counsellor associate. “So, having an AI respond that, ‘I’m here for you,’ might provide them with some sense of comfort.” 

With therapy services often being inaccessible and unaffordable for many Nigerians, Owodunni believes AI is stepping in to fill a very real gap in mental health support. “It (AI) is filling a gap. When I was working as a therapist in Nigeria, it was mostly wealthy people who had the opportunity to be in therapy.” She adds, “But the downside is that it’s fostering secrecy and stigma attached to mental health.”

Some users consider AI more dependable than a human therapist. Ore says a human therapist told her to “practice mindfulness,” following an Attention-Deficit/Hyperactivity Disorder (ADHD) diagnosis. She felt her concerns were brushed aside, so she turned to ChatGPT. “That felt more supportive as opposed to a 30-minute virtual consultation with my psychotherapist.” She insists that, unlike the vague reassurance she got in therapy, the chatbot offered a structured plan and practical ways to cope with ADHD.  

Where does the future look like?

As AI systems evolve and are trained on more complex data, fine-tuned for context, and sharpened to mimic empathy, it raises the question of how far people will go to deepen their connection to AI. Will human-AI companionship grow as these systems become more emotionally intelligent? Not everyone is excited by that possibility. 

Some users have expressed concern over AI becoming too emotionally intelligent, out of fear that it could cross boundaries that should remain human. 

Kingsley Owadara, AI ethicist and founder of Pan-african Centre for AI Ethics, believes that emotional intelligence in AI can be useful, but not in the way most people imagine. “AI could be made as a companion to people with health challenges, and could meet the specific needs of the person,” he said, pointing to cases of autistic and blind people. 

Other AI experts and developers warn against expecting too much from machines that aren’t built for the full spectrum of human care. “AI can only augment our current situation; it cannot replace psychologists,” Ajibade adds.

The concern isn’t abstract. Mental health professionals and AI experts worry that as more people turn to AI for emotional support, real-world consequences could unfold. “We’re going to have a huge problem with social interaction, with empathy, with sensitivity, with understanding people,” says Owodunni. She notes the bigger fear that widespread reliance on AI bots may “foster secrecy and the shame attached to mental health or seeking therapy services.” 

Still, for many users, the AI chatbot isn’t trying to be a therapist; it is the only space where they feel heard. “I told AI that I was tired,” Tomi says. It said, ‘I know. You’ve been carrying so much for so long. It’s okay to feel tired.’” She didn’t reply. She didn’t need to.

*Names have been changed to protect privacy.

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The hospital ward wasn’t quiet. It rarely ever was. Phones buzzed, patients coughed, nurses called out vitals, the agitated and impatient nagged, and through it all, young doctor Tobi Olatunji scribbled furiously, trying to keep up with the flood of patients. Thirty on a light day. Double when things got bad.

It was in that noise—noisy, gritty, chaotic—that Intron was born. Today, that same startup, now rebranded from Intron Health to just Intron, is making voice AI models that reportedly outperform OpenAI, Google, AWS, and Azure when it comes to recognising African accents. Intron stacks up well compared to big names, publicly available benchmarks and datasets reflect.

What started as a solution to medical paperwork has morphed into a robust suite of speech tools, called Sahara, powering voice recognition in hospitals, courtrooms, call centres, and government agencies across the continent.

The premise is simple: Big Tech’s speech tools don’t understand Africa. Intron wants to fix that. But building AI for the hardest accents on Earth didn’t start in a lab. It started in Nigeria’s overstretched clinics, where physicians are lucky to have five minutes with a patient and 30 more filling out forms. Olatunji, now Intron’s CEO, saw that broken system up close and decided to do something about it, through code.

***

It’s easy to romanticise startups. But the earliest versions of Intron didn’t even work well. The first doctors who tried the speech-to-text app during the pandemic took 45 minutes to complete their notes—much slower than writing by hand. Some gave up. Others rolled their eyes. But the problem was real: hospital staff overwhelmed, errors stacking up, and patients at risk.

There’s a particularly haunting story: One Dr. Martins, the only physician at his clinic, missed a biomarker on a routine test. The patient, an elderly woman, had a heart attack a few days later. She survived, but barely. The omission wasn’t due to incompetence. He simply didn’t have time.

It was stories like that—and countless others—that pushed Olatunji and his co-founder, Olakunle Asekun, to go deep on speech recognition. Not just adapting foreign tools, but training new models from scratch.

That led to the creation of AccentMix, Intron’s proprietary algorithm designed to handle one of AI’s thorniest challenges: the wild variability of human speech. So far, Sahara’s models have been trained on over 3.5 million audio clips from 18,000+ speakers across 30+ countries. The result? More than 300 African accents recognised with over 92% accuracy, the company claims.

That isn’t only better than Big Tech on paper but a practical breakthrough. For example, in Nigeria’s Ogun State Judiciary, Sahara has cut court transcription times nearly in half. In Uganda, at C-Care hospitals, patient wait times are down and documentation errors are dropping. Branch International, a notable fintech player, now uses Intron’s conversational bots in its call centres to slash queue times.

And unlike most imported models, Intron’s tools don’t stumble on African names, currencies, or medical jargon. It can transcribe “Ayinla” as easily as “John,” “₦1,250” as smoothly as “twenty dollars,” and understands “troponin” just as well as it does “temperature.”

But perhaps the most interesting part of Intron’s story is how it’s moved from a niche healthtech product to something much bigger: voice infrastructure for the continent.

Earlier this year, Intron launched Sahara-Optimus (its general-purpose voice recognition engine), Sahara-TTS (a pan-African text-to-speech system), and Sahara-Voice-Lock (voice authentication for security use cases).

It’s also training Sahara-Titan, a model that can understand, transcribe, and translate across 20 major African languages including Swahili, Hausa, and Zulu. These efforts have gone from research experiments to products shipping now.

It’s a shift that mirrors how platforms like Google started with search, or Amazon with books. Intron began with hospitals, but the engine it’s building is far more universal. “We built for the hardest environment first,” says Olatunji. “Now, our technology scales effortlessly.”

***

Intron isn’t the only startup working on African voice tech, but not many are doing it at this scale or with this data. And while the team still numbers under 20, the traction is real. Intron now serves 40+ organisations across 8 countries, and its models are deployed in healthcare, justice, finance, and youth health initiatives like Audere’s reproductive chatbot in South Africa.

After a USD 1.6 M pre-seed round in 2024, Intron began expanding both its cloud-native and on-prem deployment capabilities—critical in regions with patchy internet—and growing its engineering and research teams. It also joined NVIDIA’s Inception programme and partnered with the Gates Foundation, Google Research, and Digital Square to benchmark global language models across Africa.

Still, challenges persist. Data collection at scale is expensive. Local hardware constraints remain. And global competition is real. While Intron beats the big names on African voice recognition today, OpenAI, Meta, and Google could close the gap quickly. But this is where Intron’s focus becomes its superpower as Big Tech builds for everyone but Intron is Africa-first.

More than two billion people worldwide are underserved by today’s voice AI. For most of them, English isn’t their first language. For many, the tools built in Silicon Valley don’t even work.

That’s not merely an annoyance but a harbinger of real danger. It means errors in clinical notes. Misunderstood legal testimony. Frustrated customers. Lost time. In places where time is a matter of life and death, that gap can’t be shrugged off.

Intron seems on track to build infrastructure that works for the languages, cadences, and constraints of African life. One dictated sentence at a time.

And while it’s still early days, the company’s trajectory shows what happens when you start with the right problem and build deep. Not to catch up with Big Tech, but to leapfrog it on Africa’s terms.

The post An Unlikely AI Startup Born In Nigerian Hospitals Is Doing What Big Tech Still Can’t appeared first on WeeTracker.

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South African coding academy WeThinkCode has secured a USD 2 M grant from Google.org to scale its AI skills training programmes across South Africa and Kenya.

It’s a significant boost to Africa’s rising role in the global digital economy as the move signals not just philanthropic goodwill, but a strategic investment in plugging one of the continent’s most pressing talent gaps: AI readiness.

The funding will empower 12,000 learners—half of them in non-technical roles—to gain practical AI knowledge through a new curriculum designed to meet both the region’s socio-economic realities and its future-of-work ambitions.

The initiative couldn’t be more timely. According to a SAP report cited by the academy, 90% of African companies are already feeling the pain of AI skills shortages, manifesting as delayed projects, abandoned innovations, and lost business.

Founded in 2015 by Arlene Mulder, Camille Agon and Yossi Hasson, WeThinkCode has earned a reputation for its tuition-free, aptitude-based tech training model that targets youth from underserved backgrounds.

This new AI programme is an extension of that mission, with a dual-track approach. One stream will train 6,000 aspiring and early-career software engineers to integrate AI tools into their development workflows.

The other will equip 6,000 junior professionals in fields like healthcare, education, and law to use AI for everyday productivity; think automating admin tasks, synthesising data, and supercharging routine work.

Courses will be delivered in 40 to 80-hour modules, both in-person and online, with local language support built into WeThinkCode’s upgraded learning platform.

The programme will also tap into the academy’s corporate partnerships in finance, telecoms, and tech consulting to help learners showcase their new capabilities—and crucially, get hired.

The grant also positions Google among a growing list of tech giants and VCs betting on Africa’s AI potential. Last year, Nigerian startup JADA raised USD 1 M to train mid-career data professionals in AI leadership roles. Taken together, these efforts suggest that Africa’s AI talent pipeline is coming together.

“We don’t just want to prepare young people for jobs,” said Nyari Samushonga, CEO of WeThinkCode. “We want them to shape the future of work itself.”

The post Africa’s Fledgling AI Hopes Get USD 2 M Push As Google.org Backs SA’s WeThinkCode appeared first on WeeTracker.

Eighteen months ago, Karim Jouini and Jihed Othmani were ready to retire from startup life, fresh off a nine-figure exit.

Their expense management platform, Expensya, had just been acquired by Swedish fintech Medius in a deal reportedly worth over USD 120 M—one of Africa’s largest tech acquisitions made in Tunisia.

But the pull of generative AI and a nagging sense that they had unfinished business has drawn them back into the ring.

Their new startup, Thunder Code, has raised USD 9 M in seed funding to automate and rethink software testing from the ground up using generative AI.

Led by Silicon Badia, with participation from Janngo Capital, Titan Seed Fund, and strategic angels like Roxanne Varza of Station F and Karim Beguir of InstaDeep, the round includes familiar names from the Expensya era, some of whom are former employees turned investors.

Thunder Code is betting that quality assurance (QA), an often-overlooked but crucial bottleneck in software delivery, is ripe for reinvention.

The startup’s platform uses AI “agents” to autonomously understand apps, generate and execute tests, and catch bugs, promising to cut testing time by up to 90%.

In a world obsessed with shipping faster, it’s a pitch that’s already gaining traction with pilot programs in the U.S., France, Tunisia, and Canada.

Unlike Expensya, which took years to mature, Thunder Code shipped its MVP in just six weeks. “We’re moving 10x faster this time,” Jouini says, noting that the product today is already more robust than Expensya was in year four.

The founder emphasises that from day one, they have applied hard lessons: ship fast, hire top-tier talent early, and don’t be afraid of dilution if it buys speed and expertise.

Their timing is sharp. The global software testing market is projected to top USD 100 B by 2027, yet much of it still relies on clunky, code-heavy platforms.

Thunder Code joins a growing list of startups racing to modernise testing with AI, from incumbents like Tricentis to new entrants like Nova AI, but believes its execution speed and real-world traction give it a meaningful edge.

More than just a second act, Thunder Code feels like a startup born from unfinished ambition. “We promised not to do this again,” Jouini admits. “But the opportunity felt too big to ignore.”

The post Tunisian Founders Who Sold For USD 120 M Raise USD 9 M To Do It Again—With AI appeared first on WeeTracker.

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