What counts as AI automation (and what doesn't)

First, let's be clear on the term. "AI automation" gets used loosely in Bengaluru. Some vendors call themselves AI firms when they're just setting up workflows. That's not bad—workflow automation is useful—but it's not AI.

True AI in business does one of three things:

  • Learns from past data to predict what comes next. Example: flagging which leads are most likely to buy, or which invoice is likely to have an error.
  • Understands written or spoken language. Example: chatbots that answer customer questions on WhatsApp or your website without a human stepping in. Document reading that pulls information out of invoices or contracts automatically.
  • Makes decisions in real time. Example: automatically routing customer complaints to the right department, or pausing an ad campaign if cost-per-result gets too high.

Regular workflow automation—"if this, then that"—is useful and often cheaper. But it's not AI. Don't pay AI prices for workflow tools.

The three types of vendors and what they cost

1. Big consultancies (Infosys, TCS, HCL, Deloitte, etc.)

These firms have offices all over Bengaluru. They work on large projects: ERP upgrades, supply chain automation, customer data platforms.

Cost: ₹25 lakh to ₹2+ crore for a full project. Minimum engagement is usually 3–6 months.

What you get: Dedicated team, project manager, documented processes, handover to your staff, ongoing support.

Speed: Slow. Planning and scoping alone takes 4–8 weeks. You'll write a lot of requirements documents.

When to use them: You need deep integration across multiple systems (ERP, CRM, HR tool, warehouse system). You have budget and can wait 4+ months. You need someone to hold accountable if something breaks.

When to skip them: You need something working in 4 weeks. Your problem is too small (< ₹10 lakh). You want to experiment first.

2. AI labs and boutique studios (including SiteAdda Labs)

These are smaller, focused teams. Usually 10–40 people. They live in Bengaluru's startup ecosystem and specialize in AI, chatbots, data pipelines, and automation.

Cost: ₹5 lakh to ₹20 lakh for a defined project (3 months). Or ₹50,000–₹2 lakh per month on retainer.

What you get: Custom solution built for your exact problem. Faster iteration. You talk to the actual builders, not a sales team.

Speed: 4–12 weeks depending on complexity. You'll see working prototypes in 2–3 weeks.

When to use them: You have a specific, bounded problem (a chatbot, document automation, lead scoring). You want to move fast. You need someone who understands tech but doesn't require a 10-person team.

When to skip them: You need 24/7 support and a large backup team. Your project requires coordination across 5+ external systems. You need formal SLAs and compliance audits.

3. Freelancers and small agencies (<10 people)

Solo developers, 2–3 person teams working from co-working spaces or home.

Cost: ₹30,000–₹1.5 lakh per month, or ₹3–8 lakh for a project.

What you get: Low cost, usually fast turnaround, high flexibility.

Speed: 4–8 weeks if they're good and not juggling 10 clients at once.

When to use them: Budget is tight (< ₹5 lakh). You're doing a small experiment or MVP. You already know what you want built.

When to skip them: You need ongoing support, security compliance, or formal documentation. The project is mission-critical to your business. You need someone to escalate to if your main contact quits.

Why you probably don't need a "top" firm

Bengaluru has a myth: bigger = better. It isn't true for AI automation.

A ₹2 crore project from Infosys isn't automatically better than a ₹12 lakh project from a specialist AI lab. Infosys will use more people, more meetings, and more documentation. That makes sense if you're automating a ₹50 crore supply chain. It's wasteful if you're building a chatbot to handle lead qualification.

Start with the size of your problem, not the size of your ego. A smaller firm will often:

  • Move faster (less bureaucracy).
  • Let you talk to the engineer who built it (not a PM).
  • Charge you less.
  • Admit when something won't work, instead of padding the budget.

Red flags to watch before signing

"We use the latest AI model." Models change every 6 months. What matters is whether it solves your problem. A model from 2023 might be better for your use case than the latest. Ask: will this model work for your specific data and language?

"We can build this in 2 weeks." If they're promising a complex AI system in 2 weeks, they're either lying or cutting corners. Real work takes time to plan, test, and make reliable. 3–8 weeks is normal.

No clear scope or success metric. Before you sign, you should know: what will this system do, how will we measure if it works, and what happens if it doesn't? If they can't answer, walk.

Vague about data privacy or security. Ask directly: where will our data live, who can access it, what if there's a breach? Their answer should be specific (e.g., "on AWS in Mumbai region, encrypted in transit and at rest, daily backups"). If they get evasive, that's a bad sign.

Want payment upfront in full. Reputable firms ask for 30–50% upfront, the rest on delivery and handover. If they want 100% before work starts, or 100% for a "plan" with no deliverable, be careful.

How to test before committing big money

Don't hire anyone to build your full system yet. Start small.

Step 1: Write a one-page brief. What problem are you solving? What should the system do? What data will it use? What's success?

Step 2: Ask 3 vendors to estimate the work. Send them your brief. Ask for a timeline, rough cost, and their approach. Don't expect a perfect answer—you don't know everything yet. But their answers will tell you a lot. Do they ask smart questions? Do they understand your problem? Do they overpromise?

Step 3: Pay one vendor to build a prototype (not the full thing). Budget ₹50,000–₹2 lakh for 3–4 weeks of work. Build one piece: maybe a chatbot that answers 5 types of questions, or a script that reads and classifies 100 invoices. This is real proof. If they can't deliver this, they can't deliver the full system.

Step 4: Test the prototype with your team. Does it actually work? Is it easy to use? Does it save time, or does it create new work?

Step 5: Decide to expand or move on. If the prototype works, hire the same vendor to build more. If it doesn't, you've only lost ₹50K–2L, not ₹20L.

Questions to ask before you decide

Will you train my team to maintain this? You don't want to be dependent on them forever. Good vendors will spend time documenting the system and teaching your team how it works and how to fix small issues. Bad vendors want you stuck calling them every time something breaks.

What happens after launch? Will there be bugs? How fast will you fix them? Is there a support plan? For how long? What does it cost? This matters more than you think.

If this doesn't work, what's our exit? Where does the code live (your server or theirs)? Can you download it and use it elsewhere if you fire them? The answer should be yes. If they own the code or keep it on their servers only, be very careful.

How often will the AI need to learn from new data? AI systems get stale. If it learns to classify complaints from 2024 data, it might not work as well on 2026 complaints. Good vendors will plan for retraining. Ask when and how often this happens, and what it costs.

Can I see a working example? Ask the vendor to show you a similar system they've built (with their other client's permission, anonymized). Don't take them at their word. Seeing actual work matters.

The bottom line

Bengaluru has real talent in AI and automation. The right partner exists for your budget and timeline. But "best" doesn't mean biggest. It means the vendor who understands your problem, can explain what they'll build and why, can show proof of past work, and will move at your pace—not theirs.

Start with a prototype. Spend small money first. Talk to the builders, not the salespeople. And if someone promises results in 2 weeks or wants all your money upfront, keep looking.