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Founded: 2019. Incorporated: 22 October 2019. Status: Active. Funding history: Seed round announced in October 2024, led by Venture Catalysts with participation from MARL Fund, Quant Fund, C-CAMP, Nandak Growth Catalysts and angel investors; amount undisclosed. C-CAMP also lists Aikenist in its grant-funded startup cohort. Public databases variously report total funding of $50K or $60K, but these figures are not confirmed by the company or a primary funding announcement. ([thesaasnews.com](https://www.thesaasnews.com/news/aikenist-secures-seed-funding-round/))
Funding amount: Undisclosed by the company. Acquisition: No publicly verified acquisition found. Founder LinkedIn: Ashwin Amarapuram — https://in.linkedin.com/in/ashwin-amarapuram. Venkatesh Sharma — no reliably verified personal LinkedIn URL found.

Founder background: Ashwin Amarapuram is publicly identified as Co-founder and CEO, with an IISc master's degree and previous Motorola, NXP and AllGoVision experience. Venkatesh Kempapura Sharma is a co-director from incorporation and is identified as a co-founder in a public company-history profile. Founders' cities of upbringing/schooling, family origins and approximate ages: not publicly disclosed in reliable sources. Inc42 and Wellfound identify Ashwin alone as founder, while company-history and legal-director evidence supports Ashwin and Venkatesh; discrepancy noted rather than silently resolved. ([aikenist.com](https://www.aikenist.com/careers?utm_source=openai))

Problem Statement: Radiology demand > available scanner/radiologist capacity -> long booking, scan and reporting queues -> delayed diagnosis, lower equipment utilization and lost provider revenue. Alternative solutions: add scanners and staff; outsource/teleradiology; use standalone AI algorithms; deploy integrated radiology workflow software.

UNIT METRICS
============
| Unit Metric | Number |
|---|---:|
| Active installations | 800+ sites |
| Countries deployed | 10+ countries |
| MRI acceleration | 4× faster |
| Report reduction | 60% faster |
| Stroke sensitivity | 92% |
| AI models | 12+ models |
| Employees | 28 people |
| YoY growth | 5× growth |
| Customer retention | 98% retention |
| Hardware added | 0 units |

The metrics above are company, LinkedIn or commercial-database claims and should be independently validated during diligence. “Hardware added” reflects the company's software-only/no-new-hardware positioning, not a verified capital-efficiency ratio. ([aikenist.com](https://www.aikenist.com/?utm_source=openai))

Due Diligence Segment
=====================
Market & Sector Thesis - Radiology is workflow-constrained: scanner capacity, radiologist availability, fragmented PACS/RIS and reporting delays limit imaging throughput.
Market & Sector Thesis - Integrated AI workflow platforms may capture more value than isolated detection algorithms because they connect acquisition, analysis, reporting and distribution. This is an analytical thesis, not a company-reported conclusion.
Market Sizing - Company-specific TAM/SAM/SOM was not publicly disclosed; no defensible company-specific estimate identified.
Operating Traction: Company website claims 800+ active installations across 10+ countries; LinkedIn previously cited 500+ centers. The company also claims FDA 510(k) clearance for QuickRad, ISO 13485 certification and deployments across India, the UK, US and Africa. ([aikenist.com](https://www.aikenist.com/?utm_source=openai))
Direct Competition: India-based or India-relevant radiology-AI/PACS comparables include Qure.ai, DeepTek Medical Imaging, Predible Health and CARPL. Exact comparable company size was not publicly verified for each competitor. QuickRad's FDA filing identifies DeepTek's Augmento as the predicate device, which is regulatory comparability rather than proof of direct commercial competition. ([accessdata.fda.gov](https://www.accessdata.fda.gov/cdrh_docs/pdf24/K242838.pdf))
MOAT Durability - Potential moat: integrated radiology workflow, clinical validation, hospital integrations, accumulated imaging/workflow data, regulatory clearances, domain-specific models and switching costs around PACS/RIS deployment.
MOAT Durability - Disruption risk: large PACS vendors, scanner manufacturers, cloud platforms or better-funded AI vendors could bundle equivalent capabilities; model commoditization, regulatory changes or weak clinical generalization could reduce defensibility.
Plausible probable AI models used: Verified: the company describes GAN-based MRI enhancement, multi-organ segmentation, speech recognition and multimodal foundation-model integration. Plausible but unverified implementation: CNN/U-Net-style segmentation, transformer-based vision models, retrieval-augmented or LLM-assisted report generation and rules-based workflow agents. These model-family inferences are not confirmed by the company. ([aikenist.com](https://www.aikenist.com/aikenworkstation?utm_source=openai))
Technology used — Verified: DICOM, PACS, RIS, zero-footprint web viewer, cloud/on-premise/hybrid deployment, GPU inference, AI segmentation and measurement, speech-to-text, HIPAA-oriented controls, FDA 510(k) QuickRad clearance and ISO 13485 quality-management certification. Specific cloud provider, programming languages, databases, model architectures and MLOps stack were not publicly disclosed. ([accessdata.fda.gov](https://www.accessdata.fda.gov/cdrh_docs/pdf24/K242838.pdf))

Sources:
1. Aikenist official website — https://www.aikenist.com — page crawled/updated 30 August 2026 where shown. ([aikenist.com](https://www.aikenist.com/?utm_source=openai))
2. Aikenist official legal and privacy pages — https://www.aikenist.com/legal and https://www.aikenist.com/privacy — privacy page states last updated 2026. ([aikenist.com](https://www.aikenist.com/privacy?utm_source=openai))
3. Aikenist LinkedIn company page — https://in.linkedin.com/company/aikenist — crawled 2 days ago. ([in.linkedin.com](https://in.linkedin.com/company/aikenist?utm_source=openai))
4. ZaubaCorp company record — https://www.zaubacorp.com/AIKENIST-TECHNOLOGIES-PRIVATE-LIMITED-U72900KA2019PTC128949 — record stated as of 13 July 2026. ([zaubacorp.com](https://www.zaubacorp.com/AIKENIST-TECHNOLOGIES-PRIVATE-LIMITED-U72900KA2019PTC128949))
5. U.S. FDA 510(k) decision document K242838 — https://www.accessdata.fda.gov/cdrh_docs/pdf24/K242838.pdf — dated 19 September 2024; summary prepared 22 January 2025. ([accessdata.fda.gov](https://www.accessdata.fda.gov/cdrh_docs/pdf24/K242838.pdf))
6. The SaaS News funding announcement — https://www.thesaasnews.com/news/aikenist-secures-seed-funding-round/ — updated 2 October 2024. ([thesaasnews.com](https://www.thesaasnews.com/news/aikenist-secures-seed-funding-round/))
7. C-CAMP cohort page — https://www.ccamp.res.in/incubation-TIDE-cohort — current page crawled 29 August 2026. ([ccamp.res.in](https://www.ccamp.res.in/incubation-TIDE-cohort))
8. Inc42 company profile — https://inc42.com/company/aikenist/ — crawled 2026; reports FY25 revenue of ₹2.5 crore and FY24 revenue of ₹1.7 crore. Revenue converted using ₹95.6044/USD, the 28 August 2026 closing rate: ₹25 million / 95.6044 = approximately $0.2615 million. ([inc42.com](https://inc42.com/company/aikenist/))
9. BSCIC ISO 13485 certificate — https://www.aikenist.com/brochures/BN21835%20Aikenist%20MDQMS.pdf — issued 13 April 2023; expiry shown as 12 April 2026. ([aikenist.com](https://www.aikenist.com/brochures/BN21835%20Aikenist%20MDQMS.pdf))
10. Aikenist careers page — https://www.aikenist.com/careers — crawled 2 days ago. ([aikenist.com](https://www.aikenist.com/careers?utm_source=openai))

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