Specialist AI engineering · Founder-led
We help SaaS teams integrate AI into their existing products—from LLM-powered features to reliable, production-ready workflows.
Your product. Your systems. AI that fits.
For founders, CTOs, and product teams.
01The problems we solve
The difficult part isn’t calling a model. It’s connecting the right data, handling real-world failures, and making the result useful to your customers.
Extend your existing architecture with focused features, not a separate system your team has to work around.
Give AI the right context from proprietary data, with access controls that reflect your product’s permissions.
Connect LLM APIs, your backend, and business platforms through well-defined integrations.
Replace fragile paths with tested APIs, background processing, and a clear deployment plan.
Address inconsistent responses, failed workflows, security gaps, and systems that are difficult to maintain.
02Three ways we help
Start with a focused integration, a connected workflow, or an existing system that needs production engineering.
01 / Add useful AI capabilities to your SaaS.
Build LLM-powered features that work with your existing product, customer data, and APIs.
02 / Connect the steps, not just the tools.
Build multi-step workflows that combine AI with your business systems, with human approval where it matters.
03 / Make AI systems ready for real usage.
Deploy and improve AI-powered backends with the security, testing, and operational controls they need.
Focused on existing software. Designed to work with your team.
03How we work
We work with your product and engineering team. Scope, responsibilities, commercial terms, and any ongoing support are agreed before implementation.
Discuss the users, business problem, existing stack, and what a useful result looks like.
Map the data, APIs, constraints, and risks. Agree on the technical scope and how the solution will be tested.
Build the integration, review working software together, and test realistic inputs and failure cases.
Integrate with your deployment process and document how to operate, maintain, and extend the system.
Plan any ongoing maintenance, monitoring, and improvements around your team’s needs.
04Technical expertise
We choose tools to fit your architecture and constraints—not the other way around.
Python and Rust for backend services. Django and FastAPI for Python applications. PostgreSQL, Redis, REST APIs, webhooks, and background processing.
OpenAI and other LLM APIs, retrieval-augmented generation (RAG), vector search, and tool-using agents.
Docker, cloud infrastructure, workflow orchestration, automated testing, logging, and monitoring.
05Who you’ll work with
Infinity AI Lab is a founder-led engineering business led by Sarmad Gulzar, a Python and Rust backend engineer focused on practical AI integrations for SaaS products.
Meet SarmadExperience you can verify
Sarmad brings experience building Python and Rust backends, integrating APIs and LLM-powered features, and operating cloud deployments. His previous roles include backend engineering for Triptap’s AI-powered travel platform and Fielder’s workforce-management platform.
06Before we talk
Yes. Our focus is specialist integration work alongside your existing product and engineering team. We can help define the architecture, implement a focused integration, or improve an AI feature your team already maintains.
Yes. We can review how it handles data access, model responses, failures, testing, and deployment, then agree on the engineering work needed to move it toward production.
We start by understanding your data sensitivity, tenant boundaries, access controls, and model-provider requirements. Data handling, permissions, logging, and any human approval steps are designed around those constraints. Provider policies and infrastructure choices need to be reviewed for each project.
They depend on your existing systems, the integration scope, and the testing and deployment requirements. We discuss those before proposing an engagement. We don’t promise a fixed delivery window without understanding the work.
Yes. We work remotely with B2B SaaS teams, including companies in the US, UK, Canada, and other international markets. Communication, time-zone overlap, and access requirements are discussed during scoping.
Documentation and handover are part of the delivery scope. Any ongoing support, maintenance, monitoring, or further development is agreed separately so responsibilities are clear.
Let’s talk about your product
Tell us what you’re building, what systems need to connect, and where you need engineering support.