ARC delivers decision-ready analysis in weeks, then builds the AI-native workflow behind it and hands it to your team to run.
The Problem
The performance pack, the forecast refresh, the competitive scan: every quarter it goes back to a vendor, and so does the invoice. ARC builds the workflow once, then hosts it for you or hands it to your team.
Your outsourcing bill drops, and the know-how stays with you.
Large platform programs take years to land. ARC deploys working solutions in weeks that fix the biggest gaps and carry the business until the larger program is ready.
Results this quarter, while the roadmap catches up.
Manual work fills every week, and nobody has time to figure out AI. ARC trains your team to build the workflows they need, then hands them over.
Less manual work, more time for the work that grows the business.
Work gets done faster, and clients have noticed. They ask whether you use AI, push for lower fees, or bring work in-house. Under hourly billing, every hour AI saves comes straight out of revenue. ARC helps you reprice the work so the time you save shows up as margin.
You deliver faster, and the firm keeps the savings.
Cumulative cost over two years
Services
Pick an engagement to see what it includes.
Included deliverables
Scoping & Success Criteria
Define the question, the decision it informs, and what success looks like before any work starts.
Research & Data Synthesis
Market, company, and internal data pulled into one clean, sourced fact base.
Analysis & Modeling
The core analysis and models behind the answer, built to be traceable and easy to update.
Executive Readout
A decision-ready deck and walkthrough for leadership, with a clear recommendation.
Discovery Workshop
Working sessions with your team to map how the work gets done today and where the time goes.
Use-Case Prioritization
Candidate AI use cases ranked by value, feasibility, and data readiness.
Data & Systems Audit
What data you have, where it lives, how clean it is, and what it will take to use it.
ROI Business Case
What it costs to build and run, what it saves, and whether it is worth doing.
AI Roadmap
Which use cases to tackle first, in what order, what each one needs, and a realistic timeline for each.
Working Prototype
A usable version your team can test with real inputs, built in weeks.
Evaluation & Testing
Outputs checked against real examples, with accuracy measured and failure cases documented.
Implementation Roadmap
What it takes to run this use case in production: a go or no-go call, the integrations and data work still needed, governance, cost to build and run, and a timeline.
Workflow Automation
Repeatable AI workflows that take a process from data pull to finished output.
Systems Integration
Connections to the systems you already run, like your CRM, ERP, data warehouse, or document store.
Knowledge Base Setup
Your documents and data organized so AI can search and cite them reliably.
Agent & Prompt Design
The instructions, guardrails, and handoffs that make AI behave consistently.
Dashboards & Reporting
The views your team actually uses, connected to live data.
Governance & Data Privacy
Access controls, review steps, and data handling rules that fit how your firm manages risk.
Documentation & Handoff
Runbooks and walkthroughs so your team can run and extend what we built.
Weekly Working Sessions
A standing session with your team to keep priorities, numbers, and decisions moving.
On-Demand Analysis
Quick-turn analysis and small builds when a question comes up between meetings.
Monitoring & Iteration
Ongoing tuning as usage grows, so accuracy and adoption keep improving.
Building AI Agents
Design and ship agents that pull data, run the analysis, and draft the deliverable, with the right tools and guardrails.
Agent Teams & Orchestration
Multi-agent workflows where specialist agents research, model, and review each other's work in parallel.
Agent Harnesses & Evals
The harness around the model: context, tool permissions, test sets, and evals that prove an agent is ready for client work.
MCP & Data Connectors
Connect agents securely to your CRM, ERP, data warehouse, and document stores through MCP servers.
Context Engineering & Skills
Turn your firm's methods, templates, and know-how into reusable skills every agent and analyst can call on.
Agentic Coding for Analysts
Use coding agents like Claude Code to build models, dashboards, and automations without waiting on engineering.
Pick at least one deliverable.
Email my selectionTimelines are suggested. Each engagement is adapted to its scope.
See the Work
Demos of real consulting and analytical workflows, from raw inputs to finished deliverable.
Utilization by service line
Monthly net fees, $M
Engagement profitability, year to date
| Client | Net fees | Margin | Hours over budget |
|---|---|---|---|
| Client A | $8.40M | 28% | +4% |
| Client B | $5.10M | 31% | +2% |
| Client C | $3.60M | 22% | +9% |
| Client D | $2.90M | 6% | +34%Scope creep |
| Client E | $1.80M | 19% | +6% |
Case Studies
Mid-market PR agency
Built an AI application that produces the board financial performance report. Built-in tests and cross-checks verify every number against the source data, so the figures the board sees are never hallucinated. Reporting that took about 15 hours now runs in 30 seconds.
NY-based health supplement & hydration company
Delivered a competitive analysis and product portfolio architecture report. At a traditional consulting or market research firm, this work typically carries significant cost and a long timeline.
Boutique advisory consulting firm
Built a professional services time tracking tool and knowledge base management system for an advisory firm. After requirements gathering, pilot testing, and user feedback cycles, the platform was deployed within 2 months. It centralizes engagement economics and makes firm knowledge easier to retrieve.
Capabilities
ARC uses AI-native workflows to move quickly from messy inputs to decision-ready analysis. The work is designed around concrete business questions: where to invest, how to compete, what to model, and what to do next.
01/ 07
Where is our margin going, and what should we do about it?
Your utilization, client profitability, and engagement economics in one live view. We connect the data you already have so your team can act before the month closes.
How do we really stack up against the competition?
Public and private company comps across financials, positioning, and growth. You get analyst-grade work in days, built on a fact base your team can reuse.
What happens to our numbers if we make this call?
Revenue, profitability, and scenario models built to hold up to board and investor scrutiny. Every assumption is visible, so your team can test it and update it.
Are we charging the right price for the work, the client, and the team we put on it?
Rates benchmarked against the market, pricing models matched to each service, and discount rules tied to your new-client and margin targets. You see what each pricing decision does to margin before you sign.
Where should we grow next, and how do we win there?
Segmentation, channels, and positioning, grounded in your data and the market. You leave knowing which customers to chase and what to say to them.
Which products and services deserve more investment?
We map your portfolio against margin, growth, and the competitive landscape. Your team gets a clear call on where to invest, where to hold, and where to exit.
Where is our team’s time going, and what can AI take off its plate?
We map how the work gets done today and redesign the slow steps with AI-native workflows. Your team gets a working version in weeks, then we hand it over for your team to run and extend.
A 30-minute discovery call. Bring the work that's on your mind and we'll talk through scope, timeline, and what it would take to bring it in-house. No pitch, no pressure. If there's a fit, we'll scope an engagement. If not, you'll walk away with a clearer picture of what's possible.
Book a Discovery Call
Managing Partner
I spent close to a decade in management consulting at Grant Thornton's strategy arm, advising companies from the Fortune 500 to the mid-market.
Clients have included Microsoft, Cisco, Moody's, Aon, Gallagher, Truist Bank, Hub International, AssuredPartners and Maximus.
I also built my own consulting SaaS platform, a knowledge management system for professional services firms, and served as a Board Director for Cause Effective, a New York City nonprofit consulting organization.
ARC brings that experience together with hands‑on AI implementation, so your team gets senior judgment on a timeline measured in weeks and walks away with workflows it can run on its own.
Book a discovery call with Ken
AI & Data Science
I’ve spent a decade building AI and data science systems in regulated industries, most recently as AVP of Data Science at MetLife and before that at Revantage, a Blackstone company.
At MetLife, I turned around a claims auto-adjudication program, more than doubling the auto-adjudication rate, and reviewed 300+ global AI use cases on the enterprise AI Architecture Review Board.
At Revantage, I built a real estate data science practice from scratch, including forecasting work presented to Blackstone’s board.
I put together the agentic systems and machine learning behind workflows, so the analysis your team relies on is tested, reliable, safe, and ready to run in production.