01
Agentic AI Development
Autonomous AI systems that take actions, make decisions, and complete multi-step workflows without human intervention. From simple task automation to complex decision-making agents.
50+ Systems Shipped
Services · AI
Production-Ready AI Systems. From Concept to Deployment.
We build AI products that go live, serve real users, and scale with your business. From agentic workflows to voice AI to computer vision - we've shipped 50+ production AI systems since ChatGPT launched.
Trusted by 100+ AI teams
Our AI Capabilities
End-to-End AI Product Development
Deep technical expertise across the full AI stack - from strategy and architecture to production deployment and continuous improvement.
02
Voice AI Implementations
Production voice AI systems for customer service, transcription, real-time translation, and conversational interfaces across phone and digital channels.
03
RAG Framework Implementations
Retrieval-augmented generation systems that ground LLM responses in your proprietary data - reducing hallucinations and improving accuracy.
04
Computer Vision AI
Computer vision systems for visual inspection, object detection, document processing, and real-time video analysis at scale.
05
Agentic Experience (AX) Design
AI-native user experiences that balance automation with human control - building trust, transparency, and intuitive interaction with autonomous systems.
06
Open Weight Model Implementations
Deploy and fine-tune open-weight models (Llama, Mistral, Falcon) for cost control, data privacy, and customization to your specific domain.
07
AI/ML Data Pipeline Management
End-to-end data pipelines for model training, real-time inference, data ingestion, transformation, and monitoring at production scale.
08
Model Fine-Tuning
Fine-tune foundation models on your proprietary data to improve accuracy, reduce latency, and optimize performance for your specific use cases.
09
LLM Integration
Integrate GPT-4, Claude, Gemini, and other frontier models into your product. Optimized prompt engineering, context management, and API orchestration.
10
AI Safety & Guardrails
Safety systems, content moderation, bias detection, and guardrails to ensure your AI behaves as intended. Critical for production deployments serving real users.
11
Model Evaluation
Rigorous evaluation frameworks to measure accuracy, performance, and safety before deployment. Custom benchmarks tailored to your domain.
Who We Help
AI for Every Product Stage
Stage 01
Idea Stage
Validate and ship your first product. From idea to live MVP in 4 weeks - ready for real users, real feedback, real traction.
From $10K one-time
Learn more
Stage 02
Seed Stage
Iterate from MVP to product-market fit. A dedicated team builds while you sell - adding features, optimizing performance, evolving with the market.
From $12K/month
Learn more
Stage 03
PMF Stage
Extend your team without the overhead. Specialist engineers, designers, and PMs who embed directly into your team and work like in-house hires.
From $3K/month per hire
Learn more
Stage 04
Scale Stage
A team that's actually yours - your own entity, your own payroll, recruited and run by us until you're ready to take the keys.
Talk to us
Learn moreCase Studies
AI Products We've Built
Client name withheld
Breaking the Language Barrier in Healthcare with Real-Time AI Translation
End-to-end HIPAA-compliant engineering for a US health-tech company building a real-time clinical translation engine - sub-second latency, hallucination detection, and edge-case-language support, all in production.
50,000+ voice minutes of real-time medical translation per month
Stitch (StitchCare)
Reimagining Post-Transplant Care Coordination with Stitch
Tequity has been Stitch's product partner from MVP through a strategic pivot into post-transplant care - building AI-powered care coordination tools that combine modular care plans, voice calling, and care-coordinator oversight of every patient response.
MVP shipped and pivot to post-transplant care delivered without losing velocity
ChargeZone
Building India's Largest EV Charging Network with ChargeZone
Tequity owns end-to-end product, design, and engineering for ChargeZone's consumer mobile app, including a booking-flow redesign that delivered a 12-15% conversion lift and India's first EV-charging loyalty program.
13,500+ charging points managed on the platform
MonkSpaces
AI Real Estate Agent for MonkSpaces Commercial Leasing
Deployed an autonomous AI agent that qualifies leads, answers queries, and schedules tours — reducing sales team workload by 60%.
60% reduction in sales team workload
Testimonials
Founders on Working With Tequity
Pre-Seed to Series B
“We hired Tequity shortly after closing our pre-seed, and since then they've completely taken over our frontend and DevOps work. Typical turnaround is 1 day for critical bug fixes, 7 days for new features, and 6 weeks for entire MVPs. The software we built together is now used by multiple leading American biopharma companies. I recommend Tequity for any startup from angel round through Series B and beyond.”
Founder & CTO, TerraFlow
“The best outsourced engineering help you can get. Genuinely talented engineers who deliver on time, take full ownership of the product, and push back on your ideas until they understand why you're building each thing.”
Founder, Bantor
4.9/5
Average rating across 100+ customers over 4 years
“They helped us audit our product, identify key UX/UI improvement opportunities, and prioritize quick wins that delivered immediate value. The team has been responsive, collaborative, and consistently delivers high-quality work.”
Founder & CEO, Boxsy
The work behind the words.
See all case studies →
Co-Founder, QuantWheel
“We came in expecting a redesign and got something more useful. Design Labs built us a design system our AI could actually build against, so what we ship stays consistent without us having to think about it. We'd give feedback and see it reflected in the next round, often the same day.”
From the Blog
Related Reading
AI Engineering
What Is Agentic AI? A Builder's Guide
Agentic AI systems don't just respond — they plan, act, and iterate. Here's what that means in practice and how to build them.
Rahul Nair
Co-Founder & Head of Engineering
AI Engineering
Building Production Voice AI: What We've Learned
Voice AI in demos feels like magic. In production, it's a systems engineering problem. Here's what we've learned.
Rahul Nair
Co-Founder & Head of Engineering
AI Engineering
RAG vs Fine-Tuning: When to Use Each
Both approaches adapt LLMs to your domain, but they solve different problems. Here's how to choose.
Rahul Nair
Co-Founder & Head of Engineering
LET'S TALK
Ready to Build Your AI Product?
Book a 30-minute discovery call. We'll discuss your AI use case, technical requirements, and how we can help you deploy production-ready systems.