AI-Native SaaS. Built in Weeks.
We build AI-powered SaaS products — LLM integration, agentic workflows, RAG pipelines, streaming interfaces. The same stack behind briefstock.ai and feedalyze.net.
Building AI products is not like building regular software.
Most agencies bolt AI onto existing patterns — it shows
We design for AI from the first line of code. Streaming, tool calls, fallbacks — architected in, not added later
LLM latency makes UIs feel broken if not handled correctly
Every AI feature we ship uses streaming responses and loading states that feel intentional, not slow
AI API costs can spiral without usage architecture
We design prompt budgets, caching strategies, and model selection so your margins don't collapse at scale
AI output is non-deterministic — standard QA misses AI-specific bugs
We test AI features with adversarial inputs, edge-case prompts, and concurrent load — not just happy path
Switching AI providers mid-product is expensive if you're coupled to one SDK
We build provider-agnostic where possible. Your product won't break if a provider's pricing changes
AI-generated code needs human review — most shops skip this
Ara reviews every line. AI writes the boilerplate; a human reviews the logic, security, and edge cases
briefstock.ai
AI stock research reports
briefstock.ai runs real Python financial calculations and passes the results to Claude API for analyst-quality narration. AI does the communication. Python does the math. Here's what that looks like live.
Visit live →<60s
briefstock.ai generates an 8-section stock research report
4,500+
US stocks covered with real DCF and FCF calculations
0–100
churn risk scoring on feedalyze.net using multi-signal AI analysis
2 weeks
from brief to deployed AI SaaS product
Process
How we build AI products differently:
Day 0
Brief
Intake form + 20-min alignment call. Written scope before any work starts.
Days 1–8
Build
AI-accelerated development with daily progress updates. You see the product taking shape.
Days 7–12
Review
End-to-end QA on every user flow. Edge cases tested. Bugs fixed before handoff.
Day 14
Deliver
Loom walkthrough, written docs, repo access, deployment live.
Brief
Day 0Intake form + 20-min alignment call. Written scope before any work starts.
Build
Days 1–8AI-accelerated development with daily progress updates. You see the product taking shape.
Review
Days 7–12End-to-end QA on every user flow. Edge cases tested. Bugs fixed before handoff.
Deliver
Day 14Loom walkthrough, written docs, repo access, deployment live.
Pricing
Recommended for this project
~2 weeks
- Up to 3 core features
- User authentication
- Full QA on every user flow
- Deployment to production
- Loom walkthrough + written docs
- 2-week support window
AI integration (LLM calls, streaming, prompt design) is included in the MVP tier. Vector search and agentic pipelines are scoped separately.
What you actually get vs. what most agencies deliver.
| Generic AI agency | Araho Digital | |
|---|---|---|
| AI integration | ChatGPT API wrapper with basic prompts | Prompt-engineered, streamed, with fallback handling |
| Data layer | AI estimates the numbers | Python calculates, AI narrates — accuracy guaranteed |
| Cost management | No usage architecture | Prompt budgets and caching built in from day 1 |
| QA | Happy path only | Adversarial prompt testing, concurrent load, edge cases |
| Provider lock-in | Deeply coupled to one API | Provider-agnostic where possible |
| Proof of concept | Portfolio of mockups | Three live AI products you can use right now |
Questions
Three live AI products. Same methodology. Your product next.
Book a free 20-minute call. We'll scope your AI feature set and give you a fixed price before you commit to anything.
Scope my AI product