Generative Artificial Intelligence (AI) is revolutionizing various industries by automating complex tasks, enhancing decision-making, and fostering innovation. Companies like Harvey exemplify this transformation in the legal industry. Their success highlights a broader trend: every industry will have domain-specific AIs—tailored solutions that deeply integrate with the sector’s workflows, language, and unique challenges.
At Makula, we believe that manufacturing is no exception. Just as Harvey is redefining legal work, an Industrial AI can unlock new levels of efficiency and intelligence for factories and machine manufacturers. But before we dive into that, let’s look at an example
Harvey – The AI Co-Pilot for Lawyers
Harvey, founded in 2022, specializes in AI-driven solutions for the legal industry. By embedding legal expertise directly into its AI, Harvey enhances contract analysis, legal research, and document drafting. The company’s rapid growth is reflected in its funding:
- $5M Seed Funding (Nov 2022) – OpenAI Startup Fund
- $23M Series A (Apr 2023) – Sequoia Capital
- $80M Series B (Dec 2023) – Valued at $715M
- $100M Series C (July 2024) – Valued at $1.5B
- $300M Series D (Jan 2025) – Valued at $3B
Harvey’s deep integration of legal domain knowledge into its AI makes it indispensable for law firms and in-house legal teams.
This demonstrates a clear pattern: AI isn’t generic. The most successful implementations are domain-specific, integrating deep knowledge and workflows unique to their industry.
Why Domain-Specific AI Matters
Generic AI models struggle with industry-specific terminology, workflows, and data structures. To truly add value, AI must be deeply embedded in the domain it serves. Here’s why building domain-specific knowledge into AI is crucial:
- Understanding Industry-Specific Language & Context
- Legal AI like Harvey must understand contracts, case law, and regulatory language to provide accurate recommendations.
- In manufacturing, AI must comprehend maintenance logs, machine specifications, failure patterns and industry specific research papers.
- Processing Complex, Unstructured Data
- Industrial data is often unstructured. A generic AI model cannot process these effectively without deep industry expertise.
- Automating Industry-Specific Workflows
- AI must not only retrieve information but also interpret and act on it.
- Ensuring Regulatory Compliance & Accuracy
- AI must be trained on industry-specific regulations to ensure compliance and reliability. A legal AI must align with GDPR and contract laws, just as an industrial AI must adhere to safety standards and ISO certifications.
Makula: Building the AI Platform for Industry
At Makula, we believe that every industry will have its own domain-specific AI. Just as Harvey is for legal professionals, Makula is building the AI platform for industrial companies.
With our Industrial AI Platform, we integrate deeply with manufacturing workflows, machine documentation, industry specific research and maintenance processes—providing an AI-powered assistant tailored to the needs of factories & machinery manufacturers.
The future of AI is not generic—it’s deeply specialized. And in the manufacturing sector, Makula is leading the way.
