AI development company for Bangalore SaaS & startups.

We do not operate a separate Bangalore office today. Every engagement is staffed by the same senior bench out of our Mohali HQ, deliberately — it keeps the team small, stable, and senior rather than growing a satellite office we'd have to staff with juniors just to justify its overhead. For Bangalore clients who require regular on-site presence, we travel for kickoff, quarterly reviews, and major milestone demos — and for SaaS scale-ups mid-fundraise who want a technical due-diligence walkthrough in person, we schedule that on-site rather than trying to run it convincingly over a video call.

Three reasons. First, Bangalore AI talent is the highest-cost and highest-attrition market in India — hire a Bangalore-based team and there's a real chance your build gets churned mid-project when a senior engineer takes a better offer elsewhere. Second, our senior engineering bench is stable and stays on engagements end-to-end; the engineer who scopes your kickoff call is the engineer who ships your v1. Third, our delivery model — a fixed-price six-week target with the overrun cost on us — is rare among Bangalore agencies, most of which bill timesheets and leave the schedule risk sitting with you, not them.

Bangalore SaaS scale-ups typically need three things: an AI feature embedded inside an existing product without breaking the host architecture, a fast time-to-first-feature that a board update can point to, and enough engineering credibility that a CTO's own team trusts the handoff. We embed inside your codebase rather than standing up a separate AI-as-a-service dependency, ship the v1 in six weeks against acceptance criteria written before we start, and hand over architecture documents and runbooks detailed enough for your in-house engineers to extend the system without calling us for every change.

Yes. Mutual NDAs are signed before any technical detail is shared, on both sides. For pre-seed and seed-stage startups with cash constraints, we offer a discovery-pricing model — a paid two-week pilot with deliverable acceptance criteria written up front — rather than a free pitch that costs us real engineering time and commits you to nothing measurable. We do not take equity in client products under any circumstances; we are a service company, not a co-founder, and keeping the relationship purely commercial keeps the incentives aligned on shipping, not on cap-table politics.

Most SaaS v1 engagements at Aiinfox land between ₹20 lakh and ₹80 lakh ($25,000 to $100,000) fixed-price for an embedded AI feature — a copilot, a RAG system, or an agentic workflow built into your existing product. For Bangalore SaaS scale-ups building agentic copilots with custom fine-tuning and a full eval suite, engagements typically reach ₹1.5 crore over 4-6 months, inclusive of ongoing tuning and an on-call retainer through the first quarter of production traffic. Pilots are usually ₹8-15 lakh with acceptance criteria written into the scope document before kickoff.

Yes. Aiinfox is a registered Indian entity with full GST compliance. Karnataka clients receive IGST invoices, since Punjab to Karnataka is an inter-state transaction under GST rules. Payment in INR via NEFT, RTGS, or UPI is standard; international subsidiary billing is supported for Bangalore entities that are the India arm of a parent company headquartered abroad, with USD invoicing routed to the parent where that's the cleaner accounting path for both sides.

Yes. We deploy to your VPC on AWS, GCP, or Azure — including AWS ap-south-1 (Mumbai) and ap-south-2 (Hyderabad) for India data residency, since Bangalore itself isn't a hyperscaler region. Self-hosted Llama 3 on vLLM is supported for zero-egress environments where a client's security policy prohibits routing inference through a third-party API entirely. We do not require customers to use our managed cloud; full bring-your-own-cloud is standard, and for SaaS clients that already run production infrastructure, we build inside that environment rather than asking you to stand up a parallel one.

Yes. We work with Snowflake, BigQuery, Redshift, Databricks, Postgres, and ClickHouse routinely across Bangalore engagements. For Bangalore SaaS clients with mature data engineering, we slot into the existing warehouse and orchestration layer — Airflow, Prefect, dbt — rather than proposing a rebuild that serves our convenience more than your roadmap. For earlier-stage clients without an established stack, we recommend a warehouse based on actual volume and budget constraints, not vendor incentives or what's easiest for us to staff against.

Yes — it's a common inbound request in a market this competitive for engineering talent, usually because a Bangalore agency's senior engineer moved on mid-build and the replacement never caught up. Step one is a full read of what exists: the code, the data pipeline, any eval results, the prompts, and the actual production behaviour versus what the previous vendor claimed was shipped. Step two is a small, visible fix inside the first two weeks that proves we understand the system — not a re-architecture proposal that resets the clock. Step three is the honest call on what's next: keep and extend, selectively rewrite the broken pieces, or restart if the foundation can't support what you need. Most Bangalore takeovers we've handled needed the eval harness and guardrails built from scratch — the underlying product code was usually salvageable.