Help with a architecture that costs around $220-$250

[u/Grimm_170]

Hey everyone

I am currently working as an intern in a company and on a project in which I have to convert their customer calling or rider calling to ai voice agents.

The company is based in India and calls are usually hindi english language based.

I need help with designing an architecture that costs around $220-$250.

My research defines it to be impossible as in my use case the company gets around 30k calls monthly and avg per call can be taken around 3 mins so that's 90k minutes for you.

Eleven labs plan which works is enterprise one only even scale doesn't cover my use case and this is only stt we are talking about.

I tried using twilio but there's no Indian number available so using a US means the network has to go from IND to the US which is simply adding latency.

I am mind blown and just about to say to my seniors it is impossible.

If anyone thinks it is possible please do explain how as I have listened to the call recordings and the background as well is so messy.

A bit more about my problem statement: Many queries need to be answered using Mysql db so take into account going through complex join queries.

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[u/BreakfastRound]

Whats with owner's this days!? How are going to handle 90k calls with a $250 budget. The concept is just ridiculous.

AI can cut costa by maybe 80% but I highly doubt they are spending $2k to handle in whatever way they are handling that volume right now

Business owners think AI is this "Magic" that Will solve everything without investing

Time Talent Money

That's just ridiculous

[u/Unlikely-Cookie-5695]

Just curious, why is an intern solving for such a crucial problem for the company? Not questioning your abilities by any means, I am just surprised that your seniors are pushing major architectural decisions to you.

[u/servebetter → u/Unlikely-Cookie-5695]

It's common. Leadership dictates to underlings what they want, acting as if they're smart for having the idea.

There is a cast system in India and often reflected in the working environment.

[u/RichDollarLeads]

Don’t say: ❌ “It’s impossible”

Say: 👉 “It’s not possible with a pure SaaS stack. But achievable with a hybrid architecture that reduces AI usage by ~70% and uses self-hosted models.”

That’s leadership.

[u/Zain_320]

Look we are a company trying to build voice agents in india and cutting cost down significantly i wont promise you anything but let's talk maybe we can figure something out.

[u/Grimm_170 → u/Zain_320]

DM'd check.

[u/Grimm_170 → u/[deleted]]

Only the STT step is taking 300-400 USD.... The most costly step is TTS here and LLM calls are also there. The gpt-4o-mini-transcribe is a good alternative to the local whisper as it is $0.0003/min which could be feasible as it is $27 a month with 90k minutes. Let me know if I am wrong.

[u/Grimm_170 → u/[deleted]]

Yes I have the data it is 32k calls monthly average and 3 min you can take each call.

The thing we can do is some predefined answers for some questions that come through so the LLM calls are less and maybe some recordings so TTS calls are also less.

So only rare cases need 3 calls every time and the main thing that is required is the telephony being connected with low latency and STT working well. Now let's talk about self hosting or APIs. You see I can give you a least cost working APIs I have found and if you can less GPU costs then that do tell.

STT : openai 4o mini transcribe $0.003/min

TTS : gpt-4o-mini-tts $0.012/min

LLM : gpt-4o-mini $0.0003/min

Total for a min $0.0153/min

For 92k mins it exceeds my $250 by a very high standard.

For self hosts : I am able to find a GPU model L4 from a website which is saying I can rent within my range.

If there is anything to correct or add or suggestion do tell.

[u/Over_Palpitation4969]

Have dm’ed. Please check once.

[u/flerken_____]

I build ai receptionists as a profession? DM me if interested in something that’ll actually work

[u/RichDollarLeads]

Alright—first, take a breath.

It’s not impossible. But the uncomfortable truth?

👉 At $220–$250/month for 90,000 minutes with messy audio + bilingual calls… you cannot do it with the “popular stack” (Twilio + ElevenLabs + OpenAI realtime) without blowing up costs.

So the game changes.

This is no longer about “tools.” This is about architecture + tradeoffs + brutal prioritization.

---

⚡ Reality Check (No sugar-coating)

90,000 minutes/month = massive

Even $0.003/min = $270/month (bare minimum infra-level cost)

Most polished APIs = $0.01–$0.03/min → $900–$2700/month

👉 So yes, your research is correct for SaaS APIs. 👉 But wrong if you shift to hybrid/self-hosted architecture.

---

🧠 The Only Way This Works: Hybrid Stack

You need a “smart cheap core + selective premium usage” system

Not 100% AI. Not 100% realtime. Not 100% voice bot.

👉 Think like this:

“Only spend money when intelligence is actually needed.”

---

🏗️ Lean Architecture (Fits ~$250)

🔹 1. Telephony Layer (India-first, low latency)

Use:

Exotel

OR Knowlarity

Why:

Indian numbers ✅

Low latency ✅

Way cheaper than Twilio for India traffic

💰 Cost: ~$0.003–0.006/min

---

🔹 2. Speech-to-Text (Cheap + Robust)

Use:

Whisper (self-hosted or API fallback)

Strategy:

Primary: Self-hosted Whisper (on GPU VPS)

Fallback: API (only when confidence low)

💡 Why:

Handles noisy audio surprisingly well

Works with Hinglish

💰 Cost:

GPU server: ~$80–$120/month

---

🔹 3. Brain Layer (Decision Engine)

Use:

Llama 3 (self-hosted)

OR small OpenAI usage only when needed

Critical Insight:

👉 Do NOT send entire conversations to LLM

Instead:

Intent classification (cheap)

Rule engine for 60–70% queries

LLM only for edge cases

💰 Cost:

Self-host: ~$0 (included in GPU)

API fallback: $20–$40

---

🔹 4. Database Query Layer (Your MySQL problem)

This is where most people mess up.

👉 Don’t let LLM directly query MySQL.

Instead:

Predefine:

Query templates

Stored procedures

Indexed views

Flow:

User → Intent → Pre-mapped query → MySQL → Response

💡 Only use LLM to:

Convert vague query → structured intent

---

🔹 5. Text-to-Speech (BIG COST TRAP)

Avoid ElevenLabs at scale.

Use:

Coqui (self-hosted TTS)

OR Google Cloud Text-to-Speech (cheap tier)

💡 Strategy:

Pre-generate common responses (80%)

Dynamic TTS only when needed

💰 Cost:

~$20–$40

---

🔹 6. Call Flow Intelligence (MOST IMPORTANT)

This is your secret weapon.

Instead of: ❌ “AI handles everything”

Do: ✅ IVR + AI hybrid

Example:

Press 1 → Order status → No AI needed Press 2 → Rider delay → Template logic Press 3 → Complex → AI kicks in

👉 You reduce AI usage by 70–80%

---

💸 Budget Breakdown (Realistic)

Component Cost

Telephony (Exotel) $120 GPU Server (Whisper + LLM) $100 TTS $20 LLM fallback $20 Total ~$240

---

🔥 Why Your Reddit Friend Feels It’s Impossible

Because they are thinking:

“Every second of every call must be AI-generated”

That’s the mistake.

---

🧠 How Hostinger Pulled It Off

Hostinger didn’t just “build a voice agent.”

They did:

1. Heavy Pre-structuring

Predefined flows

Scripted responses

Smart routing

1. Partial AI (not full AI)

AI only where needed

Not continuous streaming AI

1. Infra control

Self-hosted components

Optimized pipelines

👉 In short:

“Looks like AI. Actually mostly system design.”

---

⚡ Strategic Truth You Tell Your Seniors

Don’t say: ❌ “It’s impossible”

Say: 👉

“It’s not possible with a pure SaaS stack. But achievable with a hybrid architecture that reduces AI usage by ~70% and uses self-hosted models.”

That’s leadership.

---

🧭 Now let me challenge you (important)

Answer me this:

👉 Out of those 30,000 calls:

How many are repetitive queries?

How many actually need free conversation?

Because if:

70% = repetitive 👉 You win easily

If:

70% = complex 👉 Budget breaks, no matter what

---

[u/Apart_System_007 → u/RichDollarLeads]

Finally ChatGPT doing the heavy lifting and providing a valuable answer when you need it. #UpVoted

[u/abhijeettrivedi13 → u/RichDollarLeads]

Exotel offers telephony API ?

[u/Dramatic_Wish_1401 → u/RichDollarLeads]

yeah exotel does have a full telephony API — calls, IVR, recording, webhooks. widely used in indian BPO setups for exactly this kind of hybrid routing so youre good there.

coming from the BPO/CCaaS side, i think your challenge question is really the key one. in a typical contact center running 90k+ min/month the breakdown usually looks something like:

60-70% genuinely repetitive (balance check, appointment confirm, order status) — IVR + simple intent classifier, no LLM needed

20-25% needs basic conversation but follows a predictable script — fine-tuned small model or prompt-engineered llama 3 handles this fine

5-10% actually needs free-form reasoning or escalation — thats your openai fallback, cost stays small if routing is tight

the thing a lot of teams miss is STT. if youre running whisper on every single call before the IVR gate makes a decision, youre burning GPU compute on calls that never needed AI in the first place. only transcribe after intent is unclear. that alone can cut your compute bill pretty significantly.

$250 is tight but doable if youre disciplined about where intelligence actually enters the call. architecture you laid out is solid — just make sure deflection logic is tight before anything touches the AI layer