Abhi Pandey
Founder & CTO
Abhi Pandey is the Founder & CTO of Brynex Labs. He leads product and engineering for Clinizy Care, the hospital management software Brynex Labs builds and runs for India's clinics and nursing homes, and for the AI agents and SaaS platforms the studio builds for clients. He writes about multi-tenant SaaS architecture, applied AI engineering, and shipping reliable systems to production.
Articles by Abhi Pandey
How We Built a Multi-Tenant HMS for Indian Clinics
We run Clinizy Care on one shared MongoDB database with shared collections: every tenant-owned document carries a tenantId, and a Mongoose plugin injects that filter into every read, write, count and aggregation, failing closed when no tenant is in context. At ₹1,999 a month for a solo clinic, a database per tenant would cost and operate out of proportion; a strict, tested guard with tenant-first indexes fits the economics.
WhatsApp Business API at Clinic Scale: What We Learned
The API call is the easy part; the system around it is the work. Sending clinic messages over the WhatsApp Cloud API for many clinics from one SaaS comes down to a sender model with a safe fallback, utility-only templates in each language you support, a queue with dead-letter handling, platform-enforced guardrails and atomic quotas, and webhooks verified against the raw request.
The DPDP Act for Health-Tech Builders: What We Built, What's Next
For health-tech builders, the DPDP Act, 2023 and the DPDP Rules, 2025 turn privacy into a product spec: itemised notices, consent as easy to withdraw as to give, minimum security safeguards with logs kept for a year, a detailed breach report to the Board within 72 hours, and working access, correction and erasure requests. The core obligations commence in May 2027. In Clinizy Care we have built India hosting, tenant isolation, role-based access, two-factor sign-in, an append-only audit trail and clinic-level export and deletion; patient-level consent, individual rights requests, field-level encryption and read auditing are next.
Lessons From Building a GST Billing Engine for Clinics
Most GST billing bugs are data bugs that surface as tax errors. Store money as integer paise, attach tax rates to the product and service master, decide CGST/SGST versus IGST in one place, back-calculate GST from MRP, apply discounts before tax, compute dates in IST, and make finalized bills immutable.
How Much Do AI Agents Cost in 2026? A Build, Run, and ROI Breakdown
A custom AI agent in 2026 can cost anything from a low-four-figure pilot to several hundred thousand dollars, depending on complexity. Brynex agent pilots start at ₹49,999 for one working workflow. This breakdown covers the three build tiers, monthly run costs, what drives price, build-versus-buy, and a worked ROI example with the math shown.
AI Agents in Business: A Practical Guide for 2026
AI agents are software that pursue a goal over multiple steps — deciding, calling tools, and checking results — instead of just answering a prompt. This guide covers what they do, real examples by function, how to start, and whether they pay off.
AI Agents vs RPA vs Zapier: Which Automation Actually Fits Your Workflow
Use Zapier for simple, rules-based app-to-app tasks, RPA for high-volume repetitive work on legacy systems, and AI agents when a workflow needs to read unstructured input and make judgment calls. The most durable setups are hybrids: deterministic tools handle the routine steps, an agent handles the decisions.
Automating Customer Support With AI Agents: A Practical Playbook
You automate customer support with AI agents by tiering tickets: let grounded agents resolve repetitive, well-documented questions and take low-risk actions, while escalating anything uncertain, emotional, or irreversible to humans. Done this way, Gartner projects 80% of common issues resolved autonomously by 2029, cutting costs 30%.
AI Agent Readiness Checklist: 12 Things Your Business Needs Before You Build
Your business is ready for AI agents when you have a specific high-volume workflow, clean accessible data, system APIs the agent can act through, clear decision boundaries, and a named owner. This 12-point checklist shows how to assess readiness before you spend a rupee on a build.
Back-Office Automation With AI Agents: Which Workflows to Automate First
AI agents are best at high-volume, rules-based back-office work — invoice processing, reconciliation, onboarding, and recurring reports. This guide gives you a prioritization framework, an honest ROI model in rupees, and the workflows to leave with humans.
How to Build a RAG Pipeline on Your Business Knowledge (2026)
A RAG pipeline lets an AI answer from your company's own documents instead of guessing: it retrieves the most relevant passages at query time and grounds the model in them. For internal-knowledge assistants, RAG usually beats fine-tuning — it is cheaper, updates instantly, and cites its sources.
AI Agent Guardrails and Evals: Shipping Agents That Do Not Break in Production
AI agent guardrails are runtime controls that constrain what an agent can read, say, and do; evals are the tests that prove it works. Together they are how you catch hallucinations and costly mistakes before customers do, and how you land in the majority of agent projects that survive.
Multi-Agent Systems: When to Use Them (and When One Agent Is Enough)
Most teams don't need a multi-agent system yet. Use multiple AI agents only when one agent breaks along a clear seam — distinct skill domains, independent verification, or genuine parallel work. Otherwise a single well-instrumented agent is cheaper, faster, and easier to debug.
Cloud vs On-Premise in 2026: A Practical Decision Guide
For most businesses in 2026, public cloud is still the right default because it trades capital cost for speed and elasticity. On-premise wins only once your workloads become large, steady, and predictable. This guide gives you the numbers and a break-even test.
AI-Native Software Development: How Lean Teams Ship More With Fewer Engineers
AI-native software development makes AI the default at every step of the build, not an add-on. It lets small teams ship faster on the right work, but the productivity gains are real, narrow, and easy to reverse without review discipline.
From MVP to Production: A SaaS Roadmap for Founders
You take a SaaS MVP to production by clearing five readiness gates in order — prove, harden, secure, observe, then scale — not by piling on features. This roadmap covers what production-grade really means, realistic timelines, when to refactor versus rewrite, and why startups fail after a good launch.
How to Choose the Right Tech Stack for a SaaS Product in 2026
The best SaaS tech stack in 2026 is a boring one: a strongly-typed Next.js and TypeScript monolith on PostgreSQL, styled with Tailwind, on a single managed platform. For most teams it ships faster, hires easier, and accrues less technical debt than anything microservices-first.