Ashutosh Kala

During COVID, I watched friends struggle with their mental health, and even when someone privately admitted they had a problem, stigma and the cost of professional therapy stood in the way of getting help. One friend was too scared to approach university counselors specifically over privacy concerns. That gap between wanting help and having a safe, affordable way to get it is what led me to co-found Tranquil AI, an AI-powered mental wellness app, as Founder & CTO.

Over the course of a year, we grew the product to 10,000+ users, improved retention by 25% and DAU by 32%, shipped a mood-prediction engine, personalization, and a deliberately-designed gamification loop (backed by published research, not just growth hacking), and built the responsible-AI side most founders skip: encrypted chat and journal data, distress detection with escalation to real human help, and safety checks on every AI response before a user ever saw it.

The full story, including the user-research pivot that changed the product's whole approach, the trade-offs behind each feature, and what I'd do differently, is below.

Read the Full Case Study →

ION Group, Noida

Jan 2025 - Present

Technical Project Manager

• Owned delivery and stakeholder alignment for 15+ enterprise fintech programs across APAC, US, and EMEA, translating client requirements into product enhancements and implementation roadmaps that supported $2.5M+ in revenue.
• Acted as primary liaison between client stakeholders and internal product/infrastructure teams, gathering requirements, scoping features, and prioritizing onboarding of complex systems including crypto exchange integrations.
• Built and implemented project health KPIs and tracking frameworks, improving delivery visibility, enabling data-driven prioritization, early identification of at-risk projects, and reducing escalations.
• Led execution of a first-of-its-kind on-prem → cloud migration, a top-3 revenue program in ION Markets, translating business requirements into a phased technical rollout plan.
• Delivered exchange-mandated regulatory programs and product enhancements, including rollout of GRP functionality, involving database migration (PDB), infrastructure scaling, and system upgrades, reducing RMAN refresh time by ~60%.
• Identified, scoped, and developed automation solutions to eliminate repetitive workflows, saving 50+ hours per week and improving team productivity.

Tranquil AI, Vellore

Read the case study →

Jan 2024 - Jan 2025

Founder & CTO

• Built and launched an AI-powered mental wellness app 0→1, growing to 10,000+ users; used prioritization frameworks (RICE/MoSCoW) after early feature-bloat taught the team to ship fewer, higher-quality features instead of building everything at once.
• Shipped AI-driven mood prediction, personalization, and gamification (Hook Model-based habit loop) that together lifted retention by 25% and grew DAU by 32%; validated the core mood-logging loop against published clinical research before scaling it.
• Designed responsible-AI safety systems: distress detection with escalation to crisis helplines and therapist/NGO networks, a negativity check gating every AI response before it reached the user, and end-to-end encryption for chat and journal data.
• Architected and scaled backend systems (Flask, Docker, cloud infrastructure), improving API response time by ~30%, a prerequisite for shipping real-time gamification rewards and voice-to-voice interaction.
• Ran continuous user research cycles (50+ early testers → 4,000+ beta signups); a key pivot came from user feedback showing an AI that listened before advising outperformed a solution-first approach.
• Secured ₹5L pre-seed funding; showcased at Startup Mahakumbh and India AI Summit; recognized among Top 10 Student Startups in India (Cisco/Nasscom Thingqubator).
• Scaled a cross-functional team from 4 aligned co-founders to 10+ members (backend, mobile, AI, infrastructure), building delegation processes and internal documentation from scratch to keep new hires aligned on vision.

Datanutts IT Solutions, Pune

Aug 2023 - Oct 2023

Data Engineering Intern

• Built an observability tool using LLM/ML to parse server logs, detect anomalies, and suggest fixes, cutting issue resolution time by 40% and downtime by 25%.
• Added a real-time alerting layer, improving incident detection speed by 50%.

Product & Business

Product Strategy · Roadmapping · Feature Prioritization (RICE / MoSCoW) · User Research · Metrics (DAU, Retention, Engagement) · Responsible-AI / Trust & Safety Design · Stakeholder Management · Agile/Scrum

Languages and Databases

Frameworks

Tools

B.Tech. in Computer Science

July 2021 - May 2025

Relevant Coursework

• Database Management Systems
• Computer Networks
• Object Oriented Programming
• Machine Learning