New Tech We’re Exploring: AI/ML, Blockchain, or AR in Apps
As a tech-forward company, we’re always asking the same question: What’s next? The digital world continues to evolve at lightning speed, and staying ahead means more than just keeping up—it means experimenting, learning, and innovating. Over the past few quarters, our R&D and engineering teams have been diving deep into emerging technologies like Artificial Intelligence/Machine Learning (AI/ML), Blockchain, and Augmented Reality (AR). Each of these offers unique opportunities—and challenges—that are already shaping the future of app development.
Here’s a closer look at how we’re exploring these technologies, what we’ve learned so far, and where we see potential for future projects.
Why Explore Emerging Tech?
Before diving into the specifics, it’s important to understand why we’re allocating time and resources to emerging tech:
- Client Expectations Are Evolving: Many clients now request features that incorporate AI, decentralization, or immersive experiences.
- Competitive Edge: Implementing cutting-edge technologies gives us an edge in delivering innovative and future-ready products.
- Scalability & Efficiency: Some of these technologies offer operational benefits like automation, security, or enhanced UI/UX.
- Upskilling Our Teams: Exploring new tools and frameworks helps our teams grow professionally and stay relevant.
- Artificial Intelligence & Machine Learning (AI/ML)
Where We’re Using It
We’ve already started incorporating AI/ML in several real-world applications—most notably in:
- Predictive Analytics: Used in e-commerce and healthcare apps to anticipate user behavior or treatment outcomes.
- Chatbots & Virtual Assistants: For customer service and onboarding, built using tools like Dialogflow, Rasa, and OpenAI.
- Image Recognition: Integrated into field apps for scanning IDs, recognizing objects, or verifying compliance.
- Personalization Engines: Tailoring recommendations based on user behavior, similar to what Netflix and Amazon do.
What We’ve Learned
- Data is King: AI is only as good as the data feeding it. Clean, diverse, and structured data is essential.
- Model Tuning is a Skill: Pre-trained models help accelerate development, but custom tuning has a steep learning curve.
- Privacy Matters: Especially in healthcare or finance, we need to tread carefully with user data and comply with GDPR/HIPAA.
What’s Next?
We’re currently experimenting with edge AI—processing data on devices rather than the cloud—to reduce latency and improve privacy. Think real-time facial recognition or gesture control without sending data to a server.
- Blockchain Technology
Where We’re Using It
While blockchain isn’t necessary for every app, we’re exploring its use in:
- Smart Contracts: Particularly for supply chain apps where transactions can be automated securely.
- Digital Identity Verification: Decentralized IDs (DIDs) for secure logins without storing passwords.
- Tokenization: Used in loyalty programs or gated-access apps to offer transparent and secure token-based interactions.
- Secure Data Logging: Blockchain’s immutability helps in tamper-proof recordkeeping for audits and legal compliance.
What We’ve Learned
- Not a One-Size-Fits-All: Blockchain is often overhyped. It’s great for transparency and trust but may not be needed for every database or payment system.
- Gas Fees & Speed Matter: Public chains like Ethereum can be expensive and slow; alternatives like Polygon or private blockchains are more viable for enterprise use.
- Security Still Needs Work: Just because something is on-chain doesn’t mean it’s inherently secure—smart contract vulnerabilities are real.
What’s Next?
We’re testing hybrid blockchain systems that combine on-chain transparency with off-chain processing speed. For example, using blockchain for audit logs while keeping transactional logic in traditional systems.
- Augmented Reality (AR)
Where We’re Using It
AR is rapidly moving from gaming and entertainment to mainstream applications. Here’s where we’ve been experimenting:
- Virtual Try-Ons: For e-commerce clients in fashion and eyewear, allowing users to “try” products in real time.
- AR Navigation: Guiding users through physical spaces like malls or campuses with overlay directions.
- Interactive Training: Especially in healthcare and industrial apps, using AR to simulate procedures or workflows.
- 3D Product Demos: Enabling real estate clients to present virtual tours or product walkthroughs.
What We’ve Learned
- User Experience Is Everything: AR must feel natural. Poor calibration or camera usage can frustrate users.
- Device Compatibility: Not all users have high-end phones, so AR features must gracefully degrade or offer fallback options.
- Development Tools Matter: We’ve had success with Unity, ARCore, and ARKit, but cross-platform AR is still a bit fragmented.
What’s Next?
We’re building an AR SDK to streamline integration across projects. This would allow us to reuse gesture detection, spatial mapping, and object tracking features without starting from scratch every time.
Integration Challenges
Each of these technologies is powerful, but integrating them into real-world apps presents some challenges:
- Team Readiness: Not all developers are immediately ready to pick up new stacks or paradigms.
- Toolchain Overload: Juggling AI models, smart contracts, and 3D render engines means more tooling and potential compatibility issues.
- Performance: Especially on mobile devices, running heavy AI or AR features can strain resources.
- Client Education: We often need to explain trade-offs, limitations, and costs to clients interested in the “buzzwords.”
How We’re Moving Forward
Here’s how we’re approaching these emerging technologies internally:
- Sandbox Projects: We allocate 10–15% of sprint cycles for exploration or PoC (proof of concept) development.
- Learning Circles: Internal knowledge-sharing sessions where engineers demo what they’re building.
- Client Prototypes: Offering “innovation sprints” to clients who want to test emerging tech before committing to full-scale implementation.
- Hiring & Training: We’re hiring engineers with AI/AR/blockchain backgrounds and offering Udemy/Learn AI courses to the team.
Exploring AI/ML, Blockchain, and AR isn’t just a strategy—it’s a mindset. It keeps us agile, curious, and aligned with where the industry is heading. While not every app needs cutting-edge tech, being ready to implement it gives us—and our clients—a serious advantage.
The journey isn’t always smooth, and the learning curve is real. But the payoff? Smarter apps, richer experiences, and a team that’s future-ready.
