I Built a CLI That Finds Me Clients on Reddit Using AI

tl;dr — I got tired of manually scrolling Reddit for people asking "who can build me a landing page?" so I built a Rust CLI that scans subreddits, uses AI to score buying intent, and hands me a ranked list of leads. Open source, runs locally, works with Ollama or any cloud AI provider.

The Problem

I'm a freelancer. Half my clients come from Reddit — someone posts in r/SaaS or r/startups asking for help, and I reply. Simple.

Except it's not simple. The workflow looks like this:

1. Open Reddit


2. Scroll through 6 subreddits


3. Read every post


4. Ignore 95% of them


5. Maybe find 1-2 posts where someone is actually looking to hire


6. By the time you find them, 3 other freelancers already replied

It's a full-time job just to find leads. And the signal-to-noise ratio is terrible — most posts are people venting, sharing links, or asking questions they don't need help with.

I wanted a tool that does the scrolling for me and only shows me posts where someone is ready to spend money.

What Cypher Does

Cypher is a terminal tool that:

• Scans subreddits you're watching


• Filters posts by keyword match first (cheap, fast)


• Sends matching posts to AI for signal extraction (intent, budget, urgency)


• Scores each lead 0-100


• Shows you a ranked table in the terminal

You tell it what you do in one sentence. It suggests subreddits to watch and keywords to filter by. Then you just run cypher scan when you're ready to find leads.

The Stack

Language: Rust — because I wanted it fast and I wanted a single binary I could cargo install and forget about.

Reddit data: Sylvia API — a Reddit data proxy that handles rate limits, parsing, and anti-bot measures. I didn't want to build a scraper. I just wanted an API key and clean JSON. Sylvia does that.

AI layer: Hybrid — local Ollama for speed, cloud fallback (OpenAI, Groq, Gemini, OpenRouter) for when the local model isn't confident enough. You set a cloud_threshold score and anything above it gets re-analyzed by a stronger model.

Database: SQLite — stores leads locally at ~/.local/share/cypher/leads.db. No cloud, no accounts, no tracking.

How It Works Under the Hood

1. Profile Setup

You run cypher init and describe what you do:

I build landing pages for SaaS startups

Cypher takes that sentence, sends it to your configured AI provider, and gets back:

• A list of subreddits where your clients hang out


• Keywords to filter posts by

For "landing pages for SaaS startups," it might suggest:

• r/SaaS, r/startups, r/webdev, r/Entrepreneur, r/smallbusiness


• Keywords: "landing page," "need a website," "looking for designer," "conversion"

2. Scan Pipeline

cypher scan

This is the core loop:

Fetch recent posts from watched subreddits (Sylvia API)

    ↓

Keyword filter (cheap, fast — throws out 80% of posts)

    ↓

AI analysis on remaining posts

    ↓

Extract signals: intent, budget, urgency, service needed

    ↓

Score 0-100 based on signal strength

    ↓

Store in local SQLite

    ↓

Display ranked table

The keyword filter is important — it saves API calls and AI tokens. If a post doesn't contain any of your keywords, it never touches the AI layer.

3. Lead Scoring

Each lead gets a score based on:

A post like "Need a landing page done, budget $3k, launching next week" scores high. "Anyone know a good landing page builder?" scores low — they're probably looking for a tool, not a person.

4. The AI Layer

This is where it gets interesting. Cypher supports two modes:

Local (Ollama): Runs qwen3:4b locally. Fast, free, private. Good enough for most lead scoring.

Cloud fallback: When the local model's confidence is below cloud_threshold, Cypher sends the post to your first configured cloud provider (OpenAI, Groq, Gemini, or OpenRouter). If that fails, it tries the next one.

The config looks like this:

[ai]

local_model = "qwen3:4b"

ollama_url = "http://127.0.0.1:11434"

cloud_threshold = 70

openai_api_key = "sk-..."

openai_model = "gpt-4o-mini"

groq_api_key = "gsk_..."

groq_model = "llama-3.3-70b-versatile"

You don't need all of them. Just one cloud provider works. Ollama is optional — if you don't have it, everything goes through cloud.

5. Daemon Mode

If you want continuous monitoring:

cypher daemon --interval 60

Scans every 60 seconds. Good for leaving running while you work — new leads pop up in your terminal as they appear.

The Commands

cypher init          # Setup profile, API keys, subreddits

cypher scan          # One-shot scan

cypher leads         # List all leads

cypher leads --min-score 80 --status new

cypher lead <id>     # Detailed view of one lead

cypher watch r/SaaS  # Add subreddit to watchlist

cypher unwatch r/SaaS

cypher watchlist     # List all watched subreddits

cypher daemon        # Background scan loop

cypher export csv    # Export to CSV

cypher export json   # Export to JSON

cypher status        # Config and status check

Try It

# Install

cargo install --path .



# Setup

cypher init



# First scan

cypher scan

You'll need:

• Rust 1.70+


• A Sylvia API key (free tier works)


• At least one AI provider (Ollama local, or any cloud key)

What I'd Do Differently

A few things I'd change if I rebuilt this:

1. 
   Webhook alerts — instead of just terminal output, send high-score leads to Slack or Telegram. I'm building this next.


2. 
   Reply templates — store pre-written responses per subreddit. When you find a lead, one key to copy a tailored reply.


3. 
   Historical scoring — track how your lead quality changes over time. Are you getting better at finding clients, or just finding more noise?


4. 
   Multi-profile — right now it's one profile per config. If you offer multiple services, you need separate configs.

Why Open Source

I built this because I needed it. I'm not trying to turn it into a SaaS — it runs locally, on my machine, with my API keys. If you find it useful, use it. If you want to add features, open a PR.

GitHub: hidekiryuuga/cypher

Cypher is built with Sylvia API — a Reddit data proxy that handles rate limits, parsing, and anti-bot measures. If you're building anything that needs Reddit data, check it out.