AI Chipmaker SandLogic Eyes $30–40 Million Fundraise at $200 Million Valuation
India’s AI and semiconductor ecosystem is witnessing a surge of innovation, and at the forefront is SandLogic, a Bengaluru-based AI chipmaker. Founded in 2018, SandLogic has evolved rapidly from a low-code/no-code solutions provider into a full-stack AI hardware and software company. The startup is now preparing for a Series A funding round targeting $30–40 million at a $200 million valuation, a move that reflects both investor confidence and the growing importance of AI chip development in India.
This funding round could be a turning point for SandLogic, allowing it to scale operations, accelerate product development, and solidify its position in the emerging edge AI and enterprise AI hardware markets.
SandLogic’s upcoming Series A funding mirrors the growing trend of Indian startups raising capital to scale innovative solutions. Similar to companies like PeLocal, which recently secured Series A funding from Unleash Capital and Unicorn India, SandLogic is positioning itself to accelerate AI chip development and enterprise adoption. For more details on PeLocal’s funding journey, see this overview.
The Evolution of SandLogic
SandLogic’s journey began with a vision to simplify AI deployment for enterprises. Its founders—Kamalakar Devaki, Jesudas Fernandes, Radhika Kanigiri, and Ravi Kumar Rayana—recognized early on that AI workloads require specialized hardware for efficiency, speed, and low energy consumption.
- From Low-Code to AI Chips: Initially, the company offered a low-code/no-code platform aimed at democratizing AI. As enterprise clients demanded faster and more optimized solutions, SandLogic pivoted to develop its own AI chips and associated software stacks.
- Full-Stack Approach: Today, SandLogic operates as a full-stack AI solutions company. This includes hardware (AI chips), software (AI frameworks, middleware), and proprietary AI models such as Shakti, its in-house large language model (LLM).
- Strategic Vision: The company’s goal is to build efficient AI infrastructure that allows businesses to deploy AI models on-premise, at the edge, or in hybrid cloud environments without the latency, bandwidth, and privacy challenges of traditional cloud-based AI.
Key Products and Technologies
SandLogic’s technological innovations are central to its market positioning. Its current and upcoming product portfolio demonstrates a focus on high performance, low power consumption, and enterprise usability.
1. Krsna Chip: High-Performance Edge AI
The Krsna chip is SandLogic’s flagship AI processor, designed to handle high-intensity AI workloads directly on-device.
- Performance: The chip is capable of 22 trillion operations per second (TOPS), allowing complex AI models to run efficiently without reliance on remote cloud servers.
- Energy Efficiency: Krsna is optimized for low power, consuming significantly less energy than comparable AI accelerators.
- Deployment: The chip is tailored for edge AI applications, enabling real-time processing for IoT devices, smart cameras, industrial automation, and enterprise AI tasks.
- Development Stage: Krsna is currently in the prototyping phase, with test chips expected in the third quarter of the fiscal year 2027.
2. ExSLerate V2: Reusable Chip Architecture
Another major innovation is ExSLerate V2, a reusable chip design aimed at efficiency and modularity.
- Power Efficiency: Consumes less than 2 watts, making it ideal for small devices or energy-constrained environments.
- Enterprise Applications: Can run AI inference tasks for sectors like banking, healthcare, and manufacturing.
- Scalability: ExSLerate V2 supports multiple AI models on a single chip, offering flexibility for enterprise deployment.
3. Shakti LLM: Proprietary Large Language Models
SandLogic has also invested heavily in in-house AI models, including Shakti, a large language model trained for enterprise applications:
- Parameter Size: Current versions include 4 billion parameters, with an 8 billion parameter version underway.
- Agent AI Layer: SandLogic is deploying an “agent AI” layer on top of Shakti to provide task-specific intelligence for enterprises, including automated customer support, predictive analytics, and document summarization.
- Enterprise Integration: Shakti models are optimized to run on Krsna and ExSLerate V2 chips, ensuring seamless integration between hardware and software.
Market Context: India’s Semiconductor Opportunity
India has historically been a software-first nation, but the government’s push for self-reliance in semiconductors is reshaping the landscape. Initiatives such as the India Semiconductor Mission and various grants for AI chip development have created an environment where startups like SandLogic can thrive.
Key market drivers include:
- AI Adoption Across Sectors: Enterprises in India are increasingly adopting AI for automation, predictive analytics, and customer engagement. Local AI hardware can reduce reliance on foreign cloud providers.
- Edge Computing: The proliferation of IoT devices and 5G networks has increased demand for low-latency, on-device AI processing.
- Government Support: Tax incentives, grants, and initiatives supporting semiconductor fabrication and research have lowered barriers for domestic startups.
- Global Supply Chain Diversification: Geopolitical pressures have made governments and enterprises look for homegrown chip solutions to avoid dependency on a single region or supplier.
SandLogic sits at the intersection of these trends, offering a homegrown solution that meets global standards in AI chip performance and efficiency.
Investor Interest and Funding Plans
The upcoming Series A funding round is attracting attention from both domestic and international investors:
- Domestic VCs: Endiya Partners, Unicorn India Ventures, and 3one4 Capital are among the Indian firms showing strong interest.
- International Investors: Celesta Capital has indicated potential participation, highlighting global confidence in India’s AI chip market.
The target raise of $30–40 million will be used to:
- Accelerate Product Development: Completing prototyping and production of Krsna and ExSLerate V2 chips.
- Scale AI Model Training: Expanding Shakti LLM capabilities to higher parameter models.
- Expand the Team: Hiring engineers, data scientists, and operations staff to support rapid scaling.
- Enhance Go-to-Market Strategies: Strengthening partnerships with enterprise clients and system integrators.
The post-money valuation of $200 million positions SandLogic as one of the leading AI chip startups in India, reflecting investor confidence in the company’s technology, market positioning, and leadership.
Industry Implications
SandLogic’s rise signals broader trends in the Indian AI ecosystem:
- Emergence of Domestic AI Hardware: Startups are moving beyond software to develop India-made chips, bridging a critical gap in the global AI supply chain.
- Edge AI Focus: Companies are prioritizing low-latency, low-power AI solutions for real-world applications, rather than purely cloud-based AI services.
- Vertical Integration: By combining chips and proprietary AI models, startups like SandLogic can offer end-to-end enterprise solutions, differentiating themselves from global competitors.
Industry analysts note that SandLogic’s approach aligns with national priorities for AI and semiconductor self-reliance, making it an attractive partner for both public and private sector adoption.
Challenges Ahead
Despite the promise, SandLogic faces several hurdles:
- R&D Intensity: Developing high-performance chips requires substantial capital, time, and technical expertise.
- Competition: Global players like NVIDIA, AMD, and Graphcore dominate AI chip markets. SandLogic must prove its performance and cost-efficiency to compete.
- Talent Acquisition: Recruiting engineers with semiconductor and AI expertise remains a challenge in India’s competitive market.
- Regulatory Environment: Compliance with emerging AI and semiconductor regulations will be essential to avoid bottlenecks in production and deployment.
Addressing these challenges successfully will determine whether SandLogic can transition from a promising startup to a major player in global AI hardware.
Future Outlook
The Series A funding will enable SandLogic to:
- Complete Krsna and ExSLerate V2 chip rollouts by 2027.
- Expand the Shakti LLM portfolio, including specialized enterprise models.
- Build partnerships with system integrators, cloud providers, and enterprises to deploy AI solutions at scale.
- Position India as a credible AI chip development hub, contributing to the broader semiconductor ecosystem.
If SandLogic executes its roadmap effectively, it could become a flagship AI hardware company in India, competing with international players while serving the unique needs of the domestic market.
Conclusion: Pioneering India’s AI Hardware Revolution
SandLogic’s journey from a low-code/no-code startup to a full-stack AI chipmaker exemplifies India’s growing ambition in AI and semiconductors. The company’s upcoming $30–40 million Series A raise at a $200 million valuation reflects investor confidence in its technology, leadership, and market potential.
By integrating high-performance chips, proprietary AI models, and enterprise-focused solutions, SandLogic is not only preparing to transform Indian industries but also contribute meaningfully to the global AI hardware landscape.
As India continues to invest in homegrown AI infrastructure, startups like SandLogic are poised to play a pivotal role in shaping the future of edge AI, enterprise intelligence, and large-scale AI deployment.
The coming years will determine whether SandLogic can meet the high expectations of investors, clients, and the broader AI community—but the trajectory so far suggests it is well-positioned to become a key player in India’s AI chip revolution.