Why not us

When we're not the right team.

Nine situations where another vendor, an in-house build, or a different approach is the better call. We turn down about 1 in 8 engagements at discovery — these are the patterns we see in those 'no's.

You need 8+ hours of daily timezone overlap

We're based in India. Most of our clients are in the US, EU, or ANZ — that's 3–4 hours of daily overlap, max. If your engagement requires the engineer to be online during your full workday, a local agency or in-house hire is the right call.

Try instead: US/EU agencies (see /vs/agency for the comparison) or local in-house.

You want strategy decks, not code

We can do strategy phases. We do them because they end in shippable artifacts, not slides. If you genuinely want a 90-page strategy deck with no production deliverable attached, Big 4 consultancies are better at that than we are.

Try instead: Big 4 / Tier-1 consultancy. See /vs/consultancy.

Your use case is < $20K

Below $20K, the engagement-overhead math doesn't work. You'd be paying for our coordination cost, not output. Try a hourly engagement starting at 20 hours, or build it yourself with one of our free templates.

Try instead: Hourly engagement (/pricing/hourly), or our free /templates.

You're building a foundation model

We build production AI on top of foundation models. We don't train foundation models. If you're building one from scratch — pretraining, RLHF, distillation pipelines — you want a research-heavy team, not a delivery agency.

Try instead: Anthropic / OpenAI / open-source research labs.

You need fully on-prem with no cloud touchpoints

We can deploy edge gateways + cloud reasoning for hybrid. We can run open-source models on your hardware for partial on-prem. We don't operate fully air-gapped environments — that's a specialized capability we don't have.

Try instead: Defense / regulated industry specialists with air-gap experience.

Your problem isn't an AI problem

If your actual problem is a process problem, a data-quality problem, or a hiring problem, AI won't solve it — it'll usually make it worse by adding a new failure mode. We'd rather you not buy AI from us than buy AI and discover the underlying issue.

Try instead: Process consulting, data engineering, or hiring help.

You want a content-generation factory with no human review

We won't build agents that publish content without humans approving. Two reasons: quality decays without it, and brand damage from one bad output undoes months of compound value. If you're set on fully unattended generation at scale, we're not the team.

Try instead: Marketing-tech vendors who specialize in content-at-scale tradeoffs.

You haven't shipped any AI yet AND want a 10-use-case roadmap

We'd rather you ship one use case and then talk about the second. Companies that try to scope 10 use cases at once typically ship none. The strategy phase is fine; the 10-use-case sprint isn't.

Try instead: Start with /quick-wins. Then /pricing/sprint for the first build.

You won't share read-only access to your data

We can't scope honestly without seeing the shape of your data. We sign NDAs, we work in your accounts, we don't take data home. But if 'no access' is the constraint, we can't help you and shouldn't pretend we can.

Try instead: Pre-purchase consulting that works from screenshots and walkthroughs.

Timing reasons we'd defer

Maybe later, not now
Pre-PMF startups with no data, no customers, no clear use case. Wait until you have something measurable. Then come back.
Maybe later, not now
Companies in active acquisition. Wait for the deal to close. AI integration during M&A is a known nightmare.
Maybe later, not now
Companies that just had a leadership change at the C-level. Wait for the new exec to settle on strategy. Building AI for a strategy that's about to change is wasted money.

None of these you? Let's talk.

If you read this list and we didn't disqualify ourselves, the math probably works. Book the call.

Book a 20-min call →See the vs comparisons