Artificial Intelligence (AI) is revolutionising industries worldwide, automating tasks and unveiling valuable insights. However, the real challenge for many companies lies not in developing AI models, but in successfully implementing them at scale — ensuring they deliver tangible results in the real world.

What is the “Last Mile” of AI?

The “last mile” of AI refers to the crucial final phase of integrating AI solutions into an organisation’s operations. Like the most challenging stretch in logistics, this phase involves moving beyond experimentation to embed AI into business processes, products, or services. Overcoming technical, organisational, and operational hurdles is essential to ensure AI delivers genuine value.

At MOHARA, we focus on bridging the gap between AI development and real-world application. Here’s how we deliver on the promise of AI at every stage of implementation:

1. Proof of Concept (PoC): Demonstrating Feasibility

Every great AI solution begins with a proof of concept (PoC) — a small-scale, controlled experiment designed to test the feasibility of an AI solution for a specific business problem. PoCs help organisations validate ideas quickly without investing heavily in full-scale development.

How MOHARA Helps:

• Identifying Use Cases: We collaborate to find high-impact areas where AI can address your challenges.
• Rapid Prototyping: Our team swiftly builds prototypes using your data and workflows.
• Validation: We assess performance and alignment with your goals to prove viability.

Starting with a PoC provides clarity on AI’s potential in your context, enabling informed decisions for future development.

2. Minimum Viable Product (MVP): Testing in the Real World

Once a PoC has demonstrated that the AI solution is feasible, the next step is creating a minimum viable product (MVP). An MVP is a functional version of the AI solution that can be deployed in a real-world environment, albeit with limited features. The goal is to test the AI solution on a broader scale while continuing to refine its functionality based on real-world feedback.

How MOHARA helps:

• Developing core features: We focus on building out the essential features of the AI solution that are critical for delivering value in the short term.
• Integration with existing systems: MOHARA ensures seamless integration with your business’s existing technology infrastructure, allowing the AI model to operate within your workflows.
• Iterative feedback: We deploy the MVP in real-world environments, collecting user feedback, performance data, and insights to make informed improvements.

With an MVP, businesses can quickly start reaping the benefits of AI while simultaneously gathering feedback to enhance the product.

3. Extensive Product Development: Scaling AI for the Future

With MVP success, it’s time to scale your AI solution to handle more data, users, and evolving needs.

How MOHARA Helps:

• Ensuring Scalability: We design solutions that handle increasing workloads without losing performance.
• Adding Advanced Features: We integrate functionalities like automation, predictive analytics, and personalised recommendations.
• Ongoing Support: We provide continuous monitoring and optimisation to keep your AI effective.
• Security and Compliance: We ensure your AI meets all regulatory and security standards.

At this stage, AI becomes integral to your operations, driving transformative change.

Why Choose MOHARA for Last Mile AI Implementation?

At MOHARA, we’re innovative tech builders adept at navigating uncertain, rapidly evolving environments. Whether you’re a bold startup founder or a large corporation pushing industry boundaries, we bring cutting-edge expertise to your AI projects.

Why Partner with MOHARA:

• End-to-End Expertise: We guide you from PoC to MVP to full-scale AI rollouts.
• Tailored Solutions: We create custom AI solutions aligned with your unique goals.
• Comfort with Uncertainty: We thrive in uncharted territory, perfect for ambitious projects.
• Rapid Execution: Our agile approach brings AI solutions to market faster.
• User-Centric Design: We build intuitive AI tools for seamless adoption.
• Data-Driven Optimisation: We continuously refine your AI to maximise ROI.

Real-World Success: MOHARA’s AI Implementation in Action

Case Study 1:
Healthcare:

MOHARA works with a US healthcare start-up, focused on enhancing patient communication using cutting-edge AI. The goal is to convert brief, clinical notes into personalised scripts that are delivered by a digital avatar of the clinician.

By leveraging large language models (LLMs) such as OpenAI’s GPT-4 and medical-specific alternatives, we’ve created an automated pipeline that improves clarity and accessibility for patients after their visits. Our team has worked extensively on prompt engineering, LLM benchmarking, and incorporating human evaluations to refine the outputs and reduce hallucinations.

We utilised OpenAI’s “Function Calling” with the LangChain framework to trigger downstream actions and added guardrails to prevent potential errors. Additionally, experiments with fine-tuning and Retrieval-Augmented Generation (RAG) techniques have enhanced domain-specific accuracy. The solution is deployed via a lightweight Django web app, offering an innovative, tech-driven approach to better healthcare communication.

Case Study 2:
Automotive:

MOHARA collaborated with a global product data management consultancy to streamline Bill of Material (BoM) validation for complex engineering products like automobiles. The goal was to reduce the high effort and wastage seen in current validation techniques by using a large language model (LLM) as both a validation logic engine and an AI assistant to engineers. This approach allows for validation based on product definitions, inferred rules, and past BoMs, enhancing efficiency and accuracy.

Our work includes prompt engineering to teach the LLM client-specific validation rules, leveraging tools like Arize for observability and Pinecone for Retrieval Augmented Generation (RAG) from product data.

The solution also features a chatbot-style interface and secure private cloud deployment for compliance. Additionally, we’ve implemented LangChain agents to integrate LLM responses with 3rd party systems, creating a dynamic and intelligent validation process.

Case Study 3:
In Stealth Mode:

A PoC focused on building a transcription and insight extraction tool to assist government operations. The PoC aims to take uploaded audio files, transcribe them, allow for in-app text editing, and provide lightweight summarization and insights (e.g., descriptions, categories). These features are deployed behind a simple web interface with secure login to prevent unauthorised access.

The technical architecture includes a third-party transcription service integrated with a large language model (LLM) for summarization and insight extraction. Technologies such as OpenAI GPT-4 and tools like Pinecone (for embedding and retrieval of insights) are employed. The system runs on a T3 Web App deployed via Vercel, ensuring scalability. The initial scope does not include user management, analytics, or long-term storage of transcriptions, making it a focused, lean deployment to validate functionality before scaling up.

Conclusion: Unlock the Full Potential of AI with MOHARA

AI has already transformed industries, but success hinges on navigating the critical “last mile” of implementation. Whether you’re starting with a PoC, building an MVP, or scaling up, MOHARA is your trusted partner in bringing AI solutions to life. We help businesses move beyond experimentation to unlock AI’s full potential and deliver lasting value.

Ready to embark on your AI journey? Contact MOHARA to discover how we can help your business succeed with AI.

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