Intelligence Portfolio

Four ways to operationalize AI

Strategy, analytics, and pre-built workflows. Each one stands on its own. They get stronger when you run them together. Pick the layer you need today.

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AI-Curious to AI-Native

Arth Consulting

A 5-phase engagement that takes your team from "we should be doing AI" to a shipped capability. The phases: Discovery, AI Readiness Scorecard, Engagement Charter, Use-Case Canvas, and Handoff. Leadership walks away with a prioritized initiative matrix, build/buy/partner calls for each use case, and a 30/60/90-day playbook. No lock-in. You keep all the IP.

Active Engagements

A 5-person productivity SaaS in GTM transition. A 200+ dealership BMW/MINI network across Australia and New Zealand.

"This is the kind of work where you actually have to build the thing, then keep it running."
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insights
Analytics + Routing

Arth Intelligence

Ingests real session data from Claude Code and Codex CLI. Scores every interaction across four metrics: Quality, Cost, Speed, and Gate Pass. Routes work to the right model tier. Confidence Tiers (30/50/70/90%) make sure recommendations only fire when the data backs them up.

MVP, design partner access only.
TypeScript, Postgres, Drizzle, and Next.js 15.

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Agent Bundles for Claude Code

Arth Marketplace

11 bundles. 33+ specialized agents. 34+ workflow skills. 13 quality-gate hooks. We've baked methodologies from Shreyas Doshi LNO, Marty Cagan INSPIRED, McKinsey MECE, and Deloitte AI Maturity directly into the workflow itself. Distributed via GitHub. Installs in minutes.

v1.0.19 LIVE 33+ AGENTS 11 BUNDLES
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Voice Interview Coaching

RoundPass.AI

AI voice interview coaching with studio-grade audio. STAR-method coaching, speaking-pace feedback, and market-ready skill tracks calibrated for the interviews actually being run today. Built on the same Arth toolkit we use everywhere else.

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AI Productivity

Tame the tool sprawl.

Claude Code, Cursor, Codex, Kiro, and Gemini all live in their own silos by default. We help you standardize, measure, and optimize the whole toolchain in three steps.

01

Assess

Consulting Methodology

We help you figure out where you actually stand before writing a line of AI-assisted code. The Readiness Scorecard tells you what's working, what isn't, and what to do about it.

02

Standardize

Unified Toolkit

One workflow definition deploys to every AI tool your team uses. Pre-built bundles for planning, implementation, QA, and ops mean every dev gets the same baseline, no matter which tool they prefer.

03

Optimize

Intelligence Engine

Real-time scoring measures every session, learns from outcomes, and routes tasks to whichever tool is actually getting the job done. Your tool spend gets smarter every week.

Where You Stand

The AI-Native maturity journey

Five levels. We meet you where you are and help you get to the next one.

Level 1

Ad Hoc

Individual devs are experimenting with AI tools on their own.

What we add

Discovery assessment to identify the gaps.

Level 2

Emerging

Pockets of usage have formed but there are no shared standards.

What we add

Toolkit installs shared workflows across teams.

Level 3

Defined

A structured approach is in place with quality gates running.

What we add

A unified engine provides measurement.

Level 4

Managed

Tool selection is data-driven with cross-team visibility.

What we add

Dashboards and a recommendation engine.

Level 5

Optimized

AI is embedded in strategy with continuous learning loops.

What we add

Full Arth stack with intelligent routing.

Our Process

Working backwards from the outcome.

Six steps from "we have a problem" to "we have a shipped product."

1

Brainstorm

We map the pain points and opportunities across your business.

2

Ideate

Structured workshops generate AI-native concepts you can actually build.

3

Select

Each concept gets scored on impact, feasibility, and strategic alignment.

4

Prototype

A functional proof-of-concept ships in two to four weeks.

5

Validate

User testing, market signal, and a technical feasibility check tell you if it's real.

6

Ship

A production-ready v1 with monitoring and an iteration plan.

Engagement Phases

Three phases. Twelve weeks.

A typical Arth engagement runs twelve weeks across three phases. Outcomes tighten as we go.

Phase 1 · Week 1-2

Discover & Define

  • check_circleStakeholder interviews and opportunity mapping
  • check_circleMarket and competitive analysis
  • check_circleFeasibility assessment and tech selection
  • check_circleProduct brief and success metrics
Phase 2 · Week 3-6

Prototype & Validate

  • check_circleFunctional prototype with real AI capabilities
  • check_circleUser testing with target customers
  • check_circleArchitecture review and cost modeling
  • check_circleGo/no-go decision backed by data
Phase 3 · Week 7-12

Build & Ship

  • check_circleProduction-grade implementation
  • check_circleMonitoring, observability, guardrails
  • check_circleLaunch strategy and GTM support
  • check_circleHandoff with iteration roadmap
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Agent Coverage

5 AI Ecosystems

Claude Code, Cursor, Codex, Kiro, Gemini

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Scoring Engine

4-Metric Framework

Quality, Cost, Speed, Gate Pass. Scored on live session data.

savings

Cost Delegation

60x Model Spread

Haiku-class (1x) handles discovery. Opus-class (60x) handles strategy. Routed automatically.