Build vs. buy: when LLMs justify replacing SaaS tools

The reality: most in-house tools cost more over three years, fail to stay maintained, and leave your team stuck when the original builder leaves. But there are narrow cases where building wins—and the math is precise enough to decide.

When the question actually makes sense

Teams on Reddit and in tech communities have asked this directly: "Anyone used LLMs to build in-house tools just to ditch an expensive SaaS?" The honest answer isn't "always no" or "always yes"—it's "if your SaaS spend is high, scope is narrow, and you accept the maintenance burden."

The three conditions that matter:

1. Below that, the build cost eats the savings.
2. You have a senior engineer who can own the tool for 3+ years. Not a contractor, not a junior. Someone who understands architecture, security, and the business logic.
3. The tool's scope is stable and narrow. Internal dashboards, reporting layers, basic CRM for a small team, ticketing for ops. Not customer-facing, not payment-handling, not compliance-heavy.

If all three are true, keep reading. If not, the SaaS vendor's feature velocity and support will outlast your patience.

The real cost: a worked example

Let's say you're a 50-person distributor paying ₹20 lakhs/year for a CRM (Zoho, Pipedrive, or similar). You want to build an in-house system instead.

Build cost (Year 1):

• Senior engineer salary for 10 weeks: ₹18 lakhs
• Database design, architecture review, security audit: ₹2 lakhs
• Hosting (AWS, DigitalOcean): ₹1.5 lakhs/year
• Bug fixes and refinement (first 6 months post-launch): ₹5 lakhs
• Year 1 total: ₹26.5 lakhs

Ongoing cost (Years 2–3):

• Hosting: ₹1.5 lakhs/year
• Maintenance, schema changes, security patches: ₹5–6 lakhs/year (one engineer at 20–30% capacity)
• Years 2–3: ₹6.5–7.5 lakhs/year each

3-year total: ₹40–42 lakhs

Compare to SaaS:

• Year 1: ₹20 lakhs
• Year 2: ₹22 lakhs (typical 10% annual increase)
• Year 3: ₹24 lakhs
• 3-year total: ₹66 lakhs

On paper, building saves ₹24 lakhs. But this assumes:

• Your engineer doesn't leave (if they do, add ₹8–10 lakhs for knowledge transfer and stabilization).
• No major security incidents or data loss (one breach costs ₹10+ lakhs in incident response and remediation).
• No feature creep (users will ask for reports, integrations, mobile access—each costs ₹2–4 lakhs).
• No API deprecations from your dependencies (PostgreSQL, Node.js, auth libraries all evolve).

Real-world 3-year cost: ₹50–60 lakhs. The gap narrows.

Five questions to ask before you build

1. Is your annual SaaS spend above ₹15 lakhs? Below that, the build cost rarely breaks even. A ₹10 lakh/year tool takes 2–3 years to pay back, and by then you've spent ₹15–20 lakhs on maintenance.

2. Do you have a senior engineer available for 8–12 weeks full-time? Not a junior, not part-time. Someone who can own architecture, database design, security, and API decisions. LLMs accelerate scaffolding, but they don't replace judgment. If you're pulling someone off a revenue-generating project, the opportunity cost is real.

3. Is the tool's scope narrow and stable? Safe bets: internal dashboards, reporting layers, basic CRM for a small team, workflow automation, data pipelines. Risky bets: customer-facing tools, anything handling payments, systems requiring audit trails or compliance. The latter need professional maintenance and liability insurance.

4. Can you commit to 20–30% ongoing maintenance for 3+ years? This is the trap. After launch, the tool needs schema migrations, security patches, dependency updates, and feature requests. Most teams underestimate this. Budget one engineer at 1–2 days per week, forever.

5. Does the SaaS vendor lack a critical feature? Not "it would be nice to have." Something that blocks your workflow today and the vendor has no roadmap for. If you're building because you want to customize, you're building for the wrong reason—you'll spend more on customization than the SaaS license costs.

Common mistakes that sink in-house tools

Underestimating maintenance. Teams build in 10 weeks, launch, then watch the tool decay. A custom tool requires the same care as a production system: monitoring, backups, security patches, and schema migrations. Most teams don't budget for this.

Scope creep. The tool launches with a CRM. Then users ask for reporting. Then integrations. Then a mobile app. Each request adds 2–4 weeks and ₹2–3 lakhs. By Year 2, you're maintaining a system that's grown 3x beyond the original spec.

Losing the original builder. If the engineer who built the tool leaves, you lose institutional knowledge. The next engineer will rewrite parts of it. Budget ₹8–10 lakhs for knowledge transfer and stabilization.

Choosing the wrong stack. Teams pick trendy frameworks (Next.js, Remix, FastAPI) because LLMs know them well. But if your team doesn't know the stack, maintenance becomes expensive. Stick to what your team already uses.

Skipping security and compliance. A SaaS tool handles GDPR, SOC 2, and data residency. Your in-house tool doesn't. If you're handling customer data, you need encryption, audit logs, access control, and regular security audits. Budget ₹3–5 lakhs upfront, ₹1 lakh/year ongoing.

How to decide: the decision tree

If annual SaaS spend < ₹12 lakhs → Buy SaaS. The build cost doesn't pay back.

If annual SaaS spend ₹12–20 lakhs AND you have a senior engineer available AND scope is narrow → Consider building. The 3-year TCO is close; build only if you're confident in maintenance.

If annual SaaS spend > ₹20 lakhs AND the vendor lacks a critical feature AND you can commit to maintenance → Building may win. But only if you're solving a real business problem, not just saving money.

If the tool is customer-facing or handles payments → Always buy SaaS. The liability and compliance burden outweigh the cost savings.

Where LLMs actually help (and where they don't)

LLMs like Cursor or GitHub Copilot accelerate the scaffolding phase: database schema, CRUD endpoints, form validation, and boilerplate. They reduce the time from 12 weeks to 8–10 weeks. But they don't reduce the maintenance burden—that's still 20–30% of an engineer's time for three years.

LLMs also struggle with:

• Architecture decisions (they'll suggest patterns, but you need judgment).
• Security (they generate code that compiles, not code that's secure).
• Testing (they write tests, but not comprehensive ones).
• Documentation (they generate it, but it's often wrong or outdated).

The real win: LLMs let a single senior engineer build what would normally take a team of two. That's valuable, but it doesn't eliminate the maintenance cost.

When to use an ERP instead of building

If you're a distributor, manufacturer, or wholesaler considering building a custom inventory or order management system, stop. An ERP like AIVCJ's Inventory, Credit & Orders solution handles multi-warehouse stock, batch and expiry tracking, purchase and sales orders, customer credit limits, and GST invoicing. Building this yourself costs ₹30–50 lakhs and requires ongoing maintenance for compliance and tax law changes.

See how it works in a live demo of a sample FMCG distributor with 3 warehouses, 396 retailers, and 8 field reps. The demo shows offline field ordering, credit control in code, and plain-English data queries—features that would take months to build and maintain.

The checklist

Before you commit to building:

• Annual SaaS spend is > ₹15 lakhs
• You have a senior engineer available for 8–12 weeks full-time
• The tool's scope is narrow and stable (not customer-facing, not payment-handling)
• You can commit 20–30% of an engineer's time to maintenance for 3+ years
• The SaaS vendor lacks a critical feature (not just a nice-to-have)
• You've budgeted for security, testing, and documentation
• You have a plan for knowledge transfer if the original builder leaves
• You've stress-tested the 3-year TCO with realistic maintenance costs

If you check all seven boxes, building may pencil out. If you check fewer than five, buy SaaS and spend the saved time on your core business.