DEV Community: Subhendu Das

Why your AI messages shouldn't leave your machine

Subhendu Das — Fri, 31 Jul 2026 06:27:31 +0000

Every time you send a message to ChatGPT, Claude, or Gemini through their web interface, that message travels to a data center, gets processed, logged, and stored. The AI company sees it. Their infrastructure handles it. Their policies govern it.

For casual use — "write me a haiku about coffee" — this is fine. But developers are increasingly using AI for things that matter: reviewing proprietary code, debugging production incidents, discussing architecture decisions, processing customer data. The content of these conversations is sensitive, often more sensitive than the code itself.

This is why self-hosted AI matters. Not as a philosophical stance, but as a practical engineering decision.

The privacy surface area of cloud AI

When you use a cloud AI service, your data touches:

The network — Your message traverses the public internet. TLS encrypts it in transit, but it's still leaving your network.
The provider's infrastructure — Load balancers, API gateways, inference servers. Each is a potential logging point.
The provider's data policies — Most providers say they don't train on your data. But policies change. Companies get acquired. Regulations shift.
Third-party integrations — If the AI service integrates with other tools, each integration adds surface area.
Logs and monitoring — Providers log requests for debugging, billing, and abuse detection.

None of these are nefarious. They're the standard architecture of cloud services. But for sensitive workloads, each one is a risk factor.

When self-hosted AI makes sense

Your conversations contain proprietary code. If you're using Claude to review a pre-launch feature, debug a security vulnerability, or discuss architecture for a competitive product, the content is trade-secret-adjacent. Self-hosting keeps it off third-party infrastructure.

You handle regulated data. Healthcare (HIPAA), finance (SOX), legal (attorney-client privilege) — these domains have specific requirements about where data can be processed.

You're in a data-sovereignty jurisdiction. GDPR, India's DPDP Act, Brazil's LGPD — these regulations care about where data is processed and stored.

You want an audit trail you control. You know exactly what's stored, where, and for how long. You can rotate, encrypt, or delete conversation history on your own schedule.

You work with clients who ask. Enterprise clients increasingly include "where does our data go?" in vendor assessments. "It stays on our infrastructure, the only external call is to the inference API" is a clean answer.

The architecture of zero-relay AI

In a cloud AI chat:

Your device -> Internet -> Anthropic's servers -> Claude -> Anthropic's servers -> Internet -> Your device

In a self-hosted setup like Telechat:

Your phone -> Telegram/WhatsApp API -> Your server -> Anthropic API -> Your server -> Telegram/WhatsApp API -> Your phone

The messaging platform sees that you're sending messages to a bot, but the content is encrypted in transit. Anthropic's API sees the query content (they have to, for inference), but nothing else — no user metadata, no conversation history beyond what you send in the API call.

What self-hosting doesn't solve

The inference provider still sees your queries. Self-hosting eliminates the intermediary, not the provider. If you need the provider to not see your data, you need on-device models (Llama, Mistral), which is a different tradeoff.

Messaging platforms see metadata. Telegram knows you're messaging a bot. They don't see the AI processing, but they see the communication patterns.

Self-hosting adds responsibility. You're responsible for uptime, security patches, access control, and backup.

Telechat: Self-hosted Claude in practice

npm install -g telechatai && telechat init

One process on your machine. Four messaging platforms. Zero cloud relay. Conversation history in local SQLite.

It also does smart model routing (saves ~60% on API costs), per-user budget caps, and has a Desktop Bridge for approving Claude's destructive actions from your phone.

The core value proposition is simple: your AI conversations stay on your infrastructure. Not because cloud is evil, but because some conversations deserve the same care you give your source code.

telechat.fyi — Self-hosted Claude AI. Your machine, your messages.

Telechat — Claude AI on your phone. Self-hosted. No cloud relay.

Subhendu Das — Fri, 31 Jul 2026 06:27:29 +0000

Tagline

Claude AI on your phone. Self-hosted. No cloud relay.

The Problem

You want Claude AI in your messaging apps — Telegram, WhatsApp, Slack. Anthropic's Claude Code Channels does this for Telegram and Discord, but it routes everything through their cloud, requires a Pro subscription, and offers no cost controls.

What if you could run Claude on your own machine, keep every message private, control costs down to the penny, and connect to WhatsApp and Slack too?

The Solution

Telechat is a self-hosted Claude AI bot that runs on your machine and connects to Telegram, WhatsApp, Slack, and web chat simultaneously.

Install in 60 seconds:

npm install -g telechatai && telechat init

That's it. One process, four platforms, zero cloud relay.

Key Features

Smart Model Routing

Telechat analyzes each message and routes it to the cheapest Claude model that can handle it. Simple questions go to Haiku ($0.001/query). Complex reasoning goes to Opus. This saves ~60% on API costs compared to always using Sonnet.

Desktop Bridge

The feature nobody else has. When Claude Code is running on your desktop and needs human approval for a destructive action, you get a push notification on your phone. Approve or deny from Telegram or WhatsApp.

Budget Controls

Set per-user daily and monthly spending caps. Get warnings at 80%. Hard cutoff at 100%. Share Claude with your team without surprise bills.

True Privacy

Every message stays on your machine. No relay server, no telemetry, no analytics. The only external call is to Anthropic's API for inference.

Multi-Platform

Telegram, WhatsApp, Slack, and web chat — all from one process. Claude Code Channels only supports Telegram and Discord.

Who It's For

Developers who want Claude on their phone without a Pro subscription
Teams who need shared AI access with budget controls
Privacy-conscious users who want self-hosted AI
Enterprise with data sovereignty requirements
DevOps engineers who want remote approval for AI agent actions

Pricing

Telechat is free and open-source. You pay only for Anthropic API usage (bring your own key).

We added mobile approvals to our CLI AI tool -- approve Claude's destructive commands from your phone

Subhendu Das — Fri, 31 Jul 2026 06:22:29 +0000

Quick share of a feature we built into Telechat (self-hosted Claude AI bot) that's been surprisingly useful for devops workflows: Desktop Bridge with mobile approvals.

The problem

You're running Claude Code (or any Claude-powered agent) on your workstation. It's refactoring a module, running tests, deploying to staging. You step away for coffee, a meeting, or just to stretch.

Claude hits a tool call that needs human approval:

rm -rf build/ (wants to clean the build directory)
git push --force (rebase gone wrong)
kubectl delete pod (scaling decision)

Without you at the keyboard, it just... waits. For however long you're gone.

The solution

Telechat's Desktop Bridge connects your Claude Code session to your phone via Telegram, WhatsApp, or Slack. When Claude needs approval:

You get a push notification with exactly what Claude wants to execute
You see the full command and context
You tap Approve or Deny
Claude continues (or backs off)

All from your phone. No VPN, no SSH, no laptop.

Why this matters for devops

Unattended CI/CD with a human gate. Run Claude as part of your pipeline for code review, test generation, or deployment prep. Gate the destructive steps on mobile approval instead of blocking the pipeline until someone checks Slack.

Overnight tasks. Kick off a large refactoring or migration analysis before bed. If Claude needs a decision at 2 AM, you'll see it in the morning and approve from your phone. It doesn't lose context while waiting.

Pair programming while mobile. Reviewing Claude's work from your phone between meetings. Approve the good stuff, deny the risky stuff, add context via chat.

How it works

Telechat runs on your workstation alongside Claude Code. It acts as a bridge between Claude's approval prompts and your messaging app. When Claude's tool-use loop hits a human-approval checkpoint, Telechat intercepts it, formats the request, and sends it to your Telegram/WhatsApp/Slack. Your response flows back and unblocks the agent.

No cloud relay — the bridge runs locally.

Setup

npm install -g telechatai
telechat init  # interactive setup
telechat bridge --connect  # link to Claude Code

telechat.fyi | npm install -g telechatai

Curious if anyone else has solved the "approve AI actions remotely" problem differently.

Telechat: self-host Claude AI across Telegram/WhatsApp/Slack with one npm install

Subhendu Das — Fri, 31 Jul 2026 06:22:29 +0000

Built something the r/selfhosted crowd might appreciate: Telechat — a self-hosted Claude AI bot that connects to Telegram, WhatsApp, Slack, and web chat from a single process.

Why self-hosted matters here

Anthropic launched Claude Code Channels recently — Claude on Telegram/Discord, managed by Anthropic. It works great, but every message goes through their cloud. Telechat takes the opposite approach:

Runs on your machine (laptop, VPS, RPi, NAS — anything that runs Node.js or Python)
Messages flow: phone → your server → Anthropic API → back to phone
No relay server, no telemetry, no analytics
SQLite for conversation history, stored locally
The only external call is to Anthropic's chat-completions API for inference

Your messages, your hardware, your data.

Install

# npm
npm install -g telechatai && telechat init

# pip
pip install telechatai && telechat init

# Docker
docker run -v ~/.telechat:/config telechatai/telechat

telechat init walks you through an interactive setup — API key, bot tokens for whichever platforms you want, model preferences, budget limits.

What it does

Multi-platform — Telegram, WhatsApp, Slack, Web Chat. All running simultaneously from one process.
Smart model routing — Routes queries to the cheapest Claude model that handles them. Saves ~60% on API costs vs always using Sonnet.
Budget caps — Per-user daily and monthly limits. Set $5/day and forget about it.
Persistent memory — SQLite-backed. Context carries across conversations.
Desktop Bridge — If you run Claude Code on your desktop and it needs approval for a destructive action, you get a push notification on your phone. Approve/deny remotely.
Media support — Send images for analysis, generate images if you have DALL-E configured.

Resource usage

Light. Single process, ~50MB RSS idle, spikes briefly during inference calls. SQLite means no database server. The bottleneck is always the Anthropic API latency, not local compute.

Self-hosting tips

Run behind a reverse proxy (Caddy/nginx) for HTTPS if using webhooks
Telegram supports long-polling (no public IP needed) — great for home setups
WhatsApp requires the WhatsApp Business API (webhook-based, needs HTTPS)
Set up systemd/Docker restart policies for reliability

telechat.fyi | GitHub

Would love feedback from the self-hosting community. What would make this more useful for your setup?

I built a self-hosted alternative to Claude Code Channels -- here's why

Subhendu Das — Fri, 31 Jul 2026 06:14:44 +0000

When Claude Code Channels launched, I was stoked — Claude on my phone, finally. Then I hit the limitations:

Only Telegram and Discord. I live in WhatsApp (most of the world does).
Everything routes through Anthropic's servers. Fine for most people, but I work with clients who have strict data policies.
Requires Pro subscription. I was already spending less via API keys for my usage pattern.
No budget controls. I wanted to give Claude access to my team without worrying about runaway costs.

So I built Telechat — same idea (Claude on your phone), completely different architecture.

It's self-hosted. Runs as one process on your machine. Messages go from your phone → your server → Anthropic API → back. No relay, no middleware, no telemetry. Your conversations never touch any server I control.

4 platforms, not 2. Telegram, WhatsApp, Slack, and web chat. All from one process.

Smart model routing. This is the cost killer. Telechat looks at each message and routes it to the cheapest model that can handle it. "What time is it in Tokyo?" → Haiku ($0.001). "Review this PR" → Opus. In practice, ~70% of my messages hit Haiku or Sonnet. Saves about 60% vs always using Sonnet.

Per-user budget caps. Daily and monthly limits. 80% warning, hard cutoff at 100%. Essential when you're sharing with a team.

Desktop Bridge — this is the feature that keeps surprising people. When Claude Code is running on your desktop and wants to do something destructive (delete a file, run a risky command), you get a push notification on your phone. Tap approve or deny. Keep working from the couch while Claude codes at your desk.

Setup is literally:

npm install -g telechatai && telechat init

Walk through the interactive setup, add your API key and bot tokens, done.

I'm not going to pretend it's better than Channels in every way. Channels wins on zero-setup convenience and being a first-party Anthropic product. But if you need WhatsApp, want self-hosted privacy, or care about cost control, give Telechat a look.

telechat.fyi | npm install -g telechatai | pip install telechatai

Happy to answer questions. Roast the architecture, I can take it.

How Telechat routes Claude queries to save 60% on API costs

Subhendu Das — Fri, 31 Jul 2026 06:12:31 +0000

Most Claude-powered applications use a single model for everything. A "what's 2+2?" gets the same Sonnet treatment as "review this 500-line PR for security vulnerabilities." That's like taking a taxi to the mailbox.

Telechat's smart model router fixes this. It analyzes each incoming message and routes it to the cheapest Claude model that can handle it — without sacrificing quality on complex queries.

The cost problem

Claude's pricing varies dramatically by model:

Model	Input (per 1M tokens)	Output (per 1M tokens)	Relative cost
Haiku	$0.25	$1.25	1x
Sonnet	$3.00	$15.00	12x
Opus	$15.00	$75.00	60x

A typical conversational message (100 input tokens, 200 output tokens) costs:

Haiku: $0.000275
Sonnet: $0.0033
Opus: $0.0165

That's a 60x cost spread. If 70% of your messages are simple enough for Haiku and only 5% need Opus, you're massively overpaying by defaulting to Sonnet.

The routing algorithm

Step 1: Message classification

The router categorizes each message into complexity tiers:

Tier 1 (Haiku): Factual questions, simple math, translations, format conversions, quick lookups. Pattern: short messages, no code blocks, no "review/analyze/design" keywords.
Tier 2 (Sonnet): Code explanations, summaries, content generation, moderate analysis. Pattern: medium-length messages, single code blocks, "explain/summarize/write" keywords.
Tier 3 (Opus): Architecture reviews, complex multi-step reasoning, large code reviews, security analysis. Pattern: long messages, multiple code blocks, "review/architect/design/security" keywords.

Step 2: Context-aware adjustment

The router considers conversation context:

If the last 3 messages were all Tier 1, and this message is ambiguous, keep it at Tier 1
If the conversation involves code, bump ambiguous messages to Tier 2
If the user has explicitly set a model preference, respect it

Step 3: Confidence scoring

Each classification gets a confidence score. If below a configurable threshold (default: 0.7), the router defaults up one tier.

if confidence < threshold:
    tier = min(tier + 1, MAX_TIER)

Conservative by default. You'd rather overspend by $0.003 than give a bad answer.

The math

Based on 30 days of moderate use (~50 messages/day):

Without routing (all Sonnet)	With routing
~1,500 messages/month	Same
Cost: $4.95/month	Cost: $1.89/month
	Haiku: 68% of messages
	Sonnet: 27% of messages
	Opus: 5% of messages

Savings: 62%

For heavier usage (200 messages/day): $19.80 → $7.56.

Budget caps: The safety net

class BudgetTracker:
    def check_budget(self, user_id, estimated_cost):
        daily_spent = self.get_daily_spend(user_id)
        monthly_spent = self.get_monthly_spend(user_id)

        if daily_spent + estimated_cost > user.daily_limit:
            return BudgetStatus.BLOCKED
        if monthly_spent + estimated_cost > user.monthly_limit:
            return BudgetStatus.BLOCKED
        if daily_spent / user.daily_limit > 0.8:
            return BudgetStatus.WARNING

        return BudgetStatus.OK

Cost is estimated before the API call and reconciled after with actual token counts.

Configuration

{
  "routing": {
    "enabled": true,
    "default_model": "sonnet",
    "confidence_threshold": 0.7,
    "tier_overrides": {
      "code_review": "opus",
      "translation": "haiku"
    }
  },
  "budget": {
    "daily_limit_usd": 5.00,
    "monthly_limit_usd": 50.00,
    "warning_threshold": 0.8
  }
}

Force a specific model per-message: /opus Review this deployment script for security issues.

Tradeoffs

Routing adds latency. The classification pass takes 50-100ms. For Haiku queries (~300ms), that's noticeable. For Opus queries (2-5s), it's invisible.

Misroutes happen. About 3-5% of messages get routed to a model that's arguably too weak. The confidence threshold helps, but it's not perfect.

Try it

npm install -g telechatai
telechat init

telechat.fyi | Open source, free forever.

Telechat vs Claude Code Channels: Which Claude-on-mobile setup is right for you?

Subhendu Das — Fri, 31 Jul 2026 06:07:32 +0000

If you want Claude AI on your phone, you now have two real options: Claude Code Channels (Anthropic's official integration) and Telechat (an open-source, self-hosted alternative). Both solve the same problem — getting Claude into your messaging apps — but they make fundamentally different architectural choices.

This is an honest comparison. I built Telechat, so I'm biased, but I'll be upfront about where Channels is the better choice.

The quick version

Feature	Claude Code Channels	Telechat
Platforms	Telegram, Discord	Telegram, WhatsApp, Slack, Web Chat
Architecture	Cloud (Anthropic servers)	Self-hosted (your machine)
Setup time	~2 minutes	~5 minutes
Pricing	Requires Claude Pro/Max/Enterprise	Anthropic API key (pay per token)
Message privacy	Routes through Anthropic	Never leaves your machine
Model selection	Automatic	Smart routing (you configure thresholds)
Budget controls	None	Per-user daily + monthly caps
Mobile approvals	No	Yes (Desktop Bridge)
Maintenance	Zero (managed)	You manage updates

Architecture: Cloud vs Self-hosted

Channels runs on Anthropic's infrastructure. You connect your Telegram or Discord account, and messages flow through Anthropic's servers to Claude and back. This means zero infrastructure on your end, but your messages are processed on Anthropic's cloud.

Telechat runs as a single process on your machine — a laptop, a VPS, a Raspberry Pi, whatever. Messages arrive via webhooks (or long-polling for Telegram), get processed locally, hit the Anthropic API for the AI response, and go back. The only external call is to Anthropic's API for the actual Claude inference. There's no relay server, no telemetry, no middleware.

When Channels wins: You don't want to manage infrastructure. You're already paying for Claude Pro. You trust Anthropic with your messages. You just want it to work.

When Telechat wins: You have strict data policies (enterprise, healthcare, legal). You're in a region where data sovereignty matters. You want to run Claude on a VPS you control. You prefer paying per-token over a monthly subscription.

Platform coverage

This is a clear differentiator. Channels supports Telegram and Discord. Telechat supports Telegram, WhatsApp, Slack, and web chat.

If you need WhatsApp — and in India, Southeast Asia, Latin America, and much of Africa, WhatsApp is the messaging app — Channels isn't an option today. Similarly, if your team lives in Slack, Telechat integrates directly.

Cost model

Channels requires a Claude Pro subscription ($20/month) at minimum. You get the subscription's usage limits.

Telechat uses a plain Anthropic API key. You pay per token. For moderate usage (say, 50 messages/day), this often works out cheaper — especially with smart model routing.

Smart model routing

Telechat's model router analyzes each incoming message and picks the cheapest Claude model that can handle it:

Simple factual questions → Haiku (~$0.001/query)
Code explanations, summaries → Sonnet (~$0.01/query)
Architecture reviews, complex reasoning → Opus (~$0.05/query)

You configure the confidence thresholds. In practice, 70-80% of messages route to Haiku or Sonnet, cutting costs roughly 60% compared to always using Sonnet.

Desktop Bridge: The unique feature

This is Telechat's most distinctive capability. When you're running Claude Code on your desktop and it hits a tool call that needs human approval — say, it wants to delete a file or run a destructive command — Telechat sends a push notification to your phone via Telegram or WhatsApp.

You see exactly what Claude wants to do, and you tap Approve or Deny. The desktop agent continues without you being at your desk. No other tool does this.

Who should use what

Use Channels if: You want zero maintenance, you're already on Claude Pro, you only need Telegram or Discord, and you're comfortable with cloud processing.

Use Telechat if: You need WhatsApp or Slack, you want self-hosted privacy, you want granular cost control, you need the Desktop Bridge for remote approvals, or you prefer pay-per-token economics.

Show HN: Telechat – Self-hosted Claude on Telegram/WhatsApp/Slack, no cloud relay

Subhendu Das — Fri, 31 Jul 2026 06:07:30 +0000

Hey HN,

I built Telechat — a self-hosted Claude AI bot that runs on your machine and connects to Telegram, WhatsApp, Slack, and web chat simultaneously from a single process.

Why I built this

When Anthropic launched Claude Code Channels in March, I was excited — finally, Claude on my phone. But Channels only supports Telegram and Discord, routes everything through Anthropic's servers, and requires a Pro/Max subscription. I wanted something that:

Keeps every message on my machine (zero cloud relay)
Works across more surfaces (WhatsApp is essential in India/SE Asia/LatAm)
Lets me use a plain API key and control costs

So I built Telechat.

What it does

npm install -g telechatai && telechat init
# or: pip install telechatai

One command sets up config, walks you through bot tokens, and starts the process. From there:

Smart model routing — Routes each query to the cheapest Claude model that can handle it. Quick factual question? Haiku ($0.001). Architecture review? Opus. You pick the thresholds. In my usage this cuts costs ~60% vs always hitting Sonnet.
Budget caps — Per-user daily and monthly limits in dollars. 80% warning, hard cutoff at 100%. No surprise bills.
Desktop Bridge — This is the one I'm most proud of. When Claude is running a coding agent on your desktop and hits a tool call that needs approval, you get a push notification on your phone. Approve or deny from Telegram/WhatsApp while you're away from your desk. No other tool does this.
Persistent memory — SQLite-backed conversation history. Context carries across sessions.
Media generation — Send images, get analysis. Generate images via DALL-E if configured.

Architecture

Telechat runs as a single Node.js/Python process on your machine. Messages from Telegram/WhatsApp/Slack/Web arrive at local webhook endpoints (or long-polling for Telegram). They're processed locally, sent to the Anthropic API, and the response goes back. Your messages never touch any server I control. There is no cloud relay, no telemetry, no analytics.

Honest comparison with Claude Code Channels

Channels wins on: zero setup (it just works if you have Claude Pro), Anthropic-supported (it's a first-party product), no self-hosting overhead.

Telechat wins on: privacy (self-hosted), cost (API keys are cheaper than Pro for moderate usage), surfaces (4 vs 2), budget controls (Channels has none), Desktop Bridge (unique feature), and you own the deployment.

If you're already paying for Claude Pro and just want Telegram, Channels is the easier choice. If you care about privacy, cost control, or need WhatsApp/Slack, Telechat is worth the 5-minute setup.

DEV Community: Subhendu Das

Why your AI messages shouldn't leave your machine

The privacy surface area of cloud AI

When self-hosted AI makes sense

The architecture of zero-relay AI

What self-hosting doesn't solve

Telechat: Self-hosted Claude in practice

Telechat — Claude AI on your phone. Self-hosted. No cloud relay.

Tagline

The Problem

The Solution

Key Features

Smart Model Routing

Desktop Bridge

Budget Controls

True Privacy

Multi-Platform

Who It's For

Pricing

Links

We added mobile approvals to our CLI AI tool -- approve Claude's destructive commands from your phone

The problem

The solution

Why this matters for devops

How it works

Setup

Telechat: self-host Claude AI across Telegram/WhatsApp/Slack with one npm install

Why self-hosted matters here

Install

What it does

Resource usage

Self-hosting tips

I built a self-hosted alternative to Claude Code Channels -- here's why

How Telechat routes Claude queries to save 60% on API costs

The cost problem

The routing algorithm

Step 1: Message classification

Step 2: Context-aware adjustment

Step 3: Confidence scoring

The math

Budget caps: The safety net

Configuration

Tradeoffs

Try it

Telechat vs Claude Code Channels: Which Claude-on-mobile setup is right for you?

The quick version

Architecture: Cloud vs Self-hosted

Platform coverage

Cost model

Smart model routing

Desktop Bridge: The unique feature

Who should use what

Links

Show HN: Telechat – Self-hosted Claude on Telegram/WhatsApp/Slack, no cloud relay

Why I built this

What it does

Architecture

Honest comparison with Claude Code Channels

Links