StackGrit

AI that analyzes your stack and turns complexity into clarity

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The Problem

You're responsible for software you can't read

  • Your team says "2 weeks" — it takes 3 months. You can't tell why
  • A key developer quits — nobody knows what they built
  • Your outsourced partner delivers "done" — you have no way to verify
  • AI wrote half your codebase — is it actually any good?
  • An investor asks about code quality — you have no objective answer

Today, your only options: $200/hr consultants or trusting your team's self-assessment. Every tool on the market targets developers. Nobody has built the executive intelligence layer for software projects.

The Solution

An on-demand CTO advisor for your codebase

What Is StackGrit?

An AI-powered platform that connects to any code repository and produces a clear, plain-language report with actionable recommendations.

  • Translates technical reality into business decisions
  • Combines code quality, architecture, security, and team dynamics in one view
  • No technical knowledge required to understand the results
  • Interactive AI chatbot for follow-up questions — not a static PDF

Think of it as a full diagnostic workup for your software project — not just asking a doctor a question, but getting the scans, the lab results, and the treatment plan.

How StackGrit Works

1. Connect (2 minutes)

Link your GitHub repo or upload a ZIP. Read-only access

2. Analyze (~45 minutes)

AI examines code, architecture, security, and team patterns

3. Report (automatic)

Plain-language report with grades, diagrams, and priorities

4. Explore (ongoing)

Drill into findings, ask the chatbot anything about your project

What takes a consultant 2 weeks and $10K, StackGrit delivers in under an hour.

What You Get — Real Insights, Not Metrics

Examples from actual StackGrit reports:

  • Authentication secrets are publicly visible in source code — anyone with repo access can impersonate any user today
  • The project depends on one developer: 610 commits over 3 years — sole owner of search and integrations
  • Changes to the search module take ~3 days vs the team average of ~1 day — a 200% overrun
  • 77% of effort goes to bug fixes vs 23% to features — technical debt is compounding
  • Update 4 dependencies to close 14 known vulnerabilities — one-line version bumps, ~2 hours

Every finding includes why it matters, where in the code, and how long to fix.

The AI Chatbot — Ask Anything About Your Project

No competitor offers this. Ask follow-up questions in plain language:

"Why do changes to search take 3x longer?"
→ Pinpoints the exact function and explains why it's costly to modify

"What happens if Nikola leaves?"
→ Maps his sole ownership of 3 critical modules, recommends mitigation

"Show me how data flows from API to database"
→ Generates an architecture diagram on demand

"Prepare talking points for my board meeting"
→ Produces executive-ready bullet points with health grade and top risks

Who Is This For?

Audience What they care about
CEO / Board Is my project healthy? What are the top risks?
Non-technical Founder Is my investment in good shape?
Project Manager What's slowing the team? What should we fix first?
Agency Client Did I get what I paid for from my vendor?
Investor / VC Is this software asset worth investing in?
CTO / VP Eng How's our architecture and security posture?
AI-Assisted Builder Is the AI-generated code actually good?

One analysis, three layers: executive summary for leadership, technical summary for engineering, detailed analysis for deep dives.

Why Now?

A confirmed gap in the market — and a new urgency

The Convergence

Two shifts converge to create this opportunity:

  • AI is writing more code than ever — most developers now use AI coding tools, shipping faster but with less human review
  • AI-assisted code shows more logic errors and security issues than human-written code
  • The oversight gap is growing — code ships faster than teams can verify

And for the first time:

  • LLMs can now analyze entire codebases — reason across architecture, correlate git history, and produce nuanced reports
  • What required a senior consultant and 2 weeks is now possible with AI in under an hour

The demand and the technology arrived at the same time.

No Industry Standard Exists

There is no FICO score for software quality. Every evaluation relies on gut feel, vendor promises, or expensive manual audits.

  • A VC evaluating a startup asks for financials — but can't ask for a code quality score
  • A government agency accepts a software deliverable with no objective quality benchmark
  • A client evaluating a vendor asks "is it done?" but never "is it good?"
B+
Architecture
C
Security
A-
Code Quality
D+
Test Coverage
B
Team Health

If StackGrit's scoring becomes what people request — not just use — it creates a standard that's harder to displace than software alone.

The Competitive Landscape

Developer tools

SonarQube, CodeClimate, DeepSource

  • Target developers, not executives
  • No holistic project view

AI code review

CodeRabbit, Qodo, Bito

  • Analyze diffs, not projects
  • Can't detect architectural decay

Engineering analytics

Jellyfish, LinearB, Pluralsight Flow

  • Enterprise-only pricing ($$$)
  • No code analysis, just metrics

Manual alternatives

Consultants, internal audits

  • $200+/hr, slow, one-time
  • Subjective, doesn't scale

No tool combines code + team + architecture + security into one executive-readable view. That's the gap.

Business Model

Per-organization credits, not per-seat

Pricing Strategy

Free
First analysis
$$
Monthly credit subscription
Unlimited projects & users
  • Free first analysis — full report, no credit card. The product is its own best sales pitch
  • Tiered monthly subscriptions — small teams to enterprise, each tier includes more credits
  • Credits cover everything — analyses, chatbot, exports. All tiers get full access
  • Single report purchase option for one-time audits, due diligence, vendor evaluation

Fills the gap between $15/user dev tools and enterprise-only platforms. A company investment, not a per-seat cost.

Pricing Tiers

$29
Starter
$149
Team
$299
Business

Tier Who it's for What you get
Starter Solo founders, small projects ~2 analyses/month
Team Small teams, agencies ~8 analyses/month
Business Larger teams, multiple projects ~20 analyses/month

Per-seat tools cost $16–99/user/month and scale with headcount. We scale with usage, not people.

How We Grow

  • Free analysis — every report is a personalized demo. No generic landing page competes with insights about your own project
  • Built-in virality — shareable report links, embeddable score badges, social-friendly scorecards
  • Content & SEO — thought leadership, comparison pages, open-source project analyses
  • Agency partnerships — white-label reports for clients, "Powered by StackGrit" as distribution
  • Standard flywheel — buyers request reports → sellers provide them → the score becomes expected

Every growth channel is designed so that using the product creates demand for the product.

Risks & Moats

Eyes wide open

Key Risks and Mitigations

Risk Mitigation
Companies won't share code Read-only access, encrypted, auto-deleted after analysis. SOC2 roadmap, future on-premise option
AI accuracy / hallucinations Every finding links to source code with confidence scores. Users rate accuracy — improving results over time
Competition from incumbents Different audience (executives, not developers), speed to market, standard-setting moat
Token costs exceed revenue Credits scale with codebase size. Caching, model optimization, cost drops with each AI generation
False positives erode trust Dismiss/mute controls, transparent accuracy tracking, chatbot lets users interrogate any finding

Every risk has a known playbook. The biggest risk is not building it — the gap exists and someone will fill it.

Defensive Moats

Software can be replicated. Standards cannot.

  • Standard-setting — if the score becomes what people request, not just use, it's a marketplace
  • Network effects — every analysis enriches the benchmark dataset. More projects, better comparisons
  • Data advantage — aggregated quality data across industries, stacks, and team sizes
  • Executive-first UX — the entire product speaks business language. Hard to bolt onto a developer tool
  • Engineered pipeline — multi-step analysis combining code, git history, dependencies, and security. Not replicable with a single AI prompt

A VC asks "what's your StackGrit score?" the same way they ask for financials. That's when software becomes infrastructure.

Roadmap

What's working

  • GitHub integration + ZIP upload
  • Multi-step AI analysis pipeline
  • Rich reports: executive, technical, detailed
  • Health grades, diagrams, KPI trending
  • Organizations, members, shareable links

Coming next

  • AI Chatbot — ask questions about your codebase
  • Continuous analysis — track trends over time
  • Actionable findings — create GitHub/Jira issues from recommendations
  • Benchmarking — compare to similar projects

The core product and landing page are live. Next: subscriptions and AI chatbot.

Know exactly where your project stands

AI helps you build fast. We help you build with confidence.

Priit Kallas
✉ kallaspriit@gmail.com
☎ +372 5543620