# Guava > Guava is founder-led AI enablement for owner-led and mid-market US firms of roughly $5M–$50M in revenue: MSPs, IT services and consulting firms, and tech staffing firms. Based in San Francisco, CA. Guava gets the client's own team using and delivering AI on Microsoft 365 Copilot, Claude Enterprise, and ChatGPT Enterprise: it assesses, rolls out, coaches, and optimizes until the client's team runs it. Romeo Diaz does the work personally, from scope through handover. Every engagement has a fixed fee agreed in writing before work starts, and the client owns everything built. Guava is independent and multi-platform. It does not resell AI licenses, hold vendor partnerships, or take referral fees, and it recommends honestly which platform fits each team. Gemini for Google Workspace is supported for Google Workspace clients, with the same process. Custom builds run on Azure AI Foundry, Amazon Bedrock, or Google Vertex AI, usually whichever cloud the client already uses. Guava does not white-label or deliver work for a client's customers: for MSPs, it coaches the MSP's own team to deliver AI services, going from managed service provider to Managed Intelligence Provider (MIP). Larger firms ($50M–$150M) and other owner-led businesses are welcome to start with an AI Assessment. Book a 20-minute call: https://workwithguava.com/talk Email: romeo@workwithguava.com ## Engagements - AI Assessment ($4,000, 2 weeks, paid upfront and credited in full toward an AI Rollout or Implementation & Offer Launch): a review of workflows and data, a ranked list of where AI saves the team the most time, estimated costs, an honest recommendation of which platform fits each team (Microsoft 365 Copilot, Claude Enterprise, ChatGPT Enterprise, or Gemini), and a clear yes or no on what is worth building. Recommended starting point. - AI Rollout ($25,000, 3–6 weeks; $21,000 after the Assessment credit), including data readiness on any platform (Copilot Readiness on Microsoft 365): roll out Copilot, Claude Enterprise, or ChatGPT Enterprise with the client's data ready first, either as a new rollout or for licenses the client already pays for but barely uses. It runs in phases: Ready (on Microsoft 365, Copilot Readiness: a Microsoft 365 tenant review, a SharePoint and OneDrive oversharing and permissions cleanup plan, sensitivity labels and data protection basics, and pilot group selection), Activate (3–5 use cases with measured baselines, configuration and connectors), and Adopt (team training and adoption tracking). Optimize and Govern continue in Ongoing Optimization & Governance. The AI Assessment is not required first: a client who already knows what it wants can start with the Rollout, whose Ready phase then also picks the first 3–5 use cases. After an Assessment, Ready starts from the Assessment's ranked list, so nothing is assessed twice. The outcome is hours back per tech per week, measured in the client's PSA. - Implementation & Offer Launch ($35,000, 3 months; $31,000 after the Assessment credit): MSP to MIP in 90 days. Working AI use cases inside the client's systems, tested against criteria agreed up front, with custom builds on Azure AI Foundry, Amazon Bedrock, or Vertex AI where needed; the client's team learns to deliver AI services across Copilot, Claude, and ChatGPT; the client's AI services are packaged and priced for its own clients; by the end, the client's team runs it without Guava. - Ongoing Optimization & Governance ($4,000 per month, optional, cancel anytime, no minimum commitment): adoption and optimization, workflow operations, and AI governance and security: an AI acceptable-use policy, an inventory of the AI tools, connectors, and agents in use (shadow AI), access and connector reviews (Claude and ChatGPT connectors, Copilot agents, admin rights), a quarterly governance review, and incident guidance. Guava coaches the client's team to run governance itself and, for MSPs, to offer it to their own clients. ## What an AI Assessment delivers A ranked list of the client's workflows, each with estimated hours back per week, an estimated monthly AI tool cost, and a verdict: Build, Pilot, or Don't build, with the reasoning written down for every "Don't build". It ends with a recommended next step. The site shows sample pages for a fictional MSP, IT services firm, and tech staffing firm; those numbers are illustrative, not client results. ## Track record As Chief AI Officer at an SF-based tech staffing company (the client appears only under that description), from February to September 2026, Romeo helped it sell AI services to the clients it already staffed; until then, all its revenue came from placements. He hired and trained 6 full-time engineers, each delivering 3–4 projects, and set up the offer tiers (an Assessment, then an implementation, then ongoing support), the funnel, website and marketing, bi-weekly client hackathons, and a managed services team for live projects. Almost every client started with an Assessment; 2 in 3 of those became larger implementations, and 80% of the implementations stayed on for ongoing support. In production for its clients: a sales prep agent for a large tech company, a Salesforce and finance agent for a social media company, a chatbot over a finance firm's Snowflake and SharePoint data, assistant agents in Slack, Teams and WhatsApp, client onboarding automation for a wealth manager, an LLM gateway for a large accounting and audit firm, and code-review agents in GitHub Enterprise for a large networking company. A private equity firm estimated its acquisition price at 2.4x the estimate from the year before he joined; Romeo credits more recurring revenue, more revenue per employee, lower churn, and less key-person risk. ## Process 1. Scope: written before signature, covering the workflow, the measure of success, the fixed fee, an estimate of ongoing AI tool and usage costs, and the end date. 2. Access: NDAs are signed; only the access needed is requested, and everything touched is logged. Access can be revoked or given an expiry at any time. 3. Build: work happens inside the client's systems and tenant with weekly checkpoints. 4. Acceptance: the client runs the work on real tasks from their own queue and decides whether it meets the criteria. 5. Ownership: accounts, code, AI workflows, and dashboards stay in the client's environment. 6. Afterwards: optional Ongoing Optimization & Governance, month to month. ## Founder Guava is the 2026 name for Romeo Diaz's independent practice in San Francisco: 15+ years of engineering, hands-on at companies like Airbnb, Uber, and Facebook, and 5 years building AI agents and workflow automations for tech services firms at places like Google, Pinterest, and Cisco. The new name lets him add senior engineers as it grows. His background in solutions architecture, DevOps, and cloud means he knows how tech services firms actually run. He also built and maintains Main Street Bench, a private evaluation benchmark of how well AI models look after a small business: a model is handed everything for a fictional neighborhood bakery with 100 hidden problems and scored on problems fixed minus things broken. Its sibling, MSP Bench, does the same for a fictional managed IT provider, with 100 hidden problems and $1,000,000 at risk. He also publishes Guava Mode, the free, open-source plugin he runs Guava on, which gives Claude, ChatGPT and Grok Bot one shared AI context in the owner's own Notion. - LinkedIn: https://www.linkedin.com/in/romeodiazai/ - X: https://x.com/romeodiazai - Main Street Bench results: https://workwithguava.com/mainstreetbench (the test itself is private) - MSP Bench results: https://workwithguava.com/mspbench (the test itself is private) ## Pages - [Homepage](https://workwithguava.com/): the track record, engagements, fees, the AI Rollout's phases, the process with the clauses every scope includes, governance, and FAQ. - [For MSPs](https://workwithguava.com/msp): AI Rollout with Copilot Readiness, MSP to MIP, and Ongoing Optimization & Governance; MSP use cases (ticket triage, QBR prep, alert summaries, client AI policies) and an MSP sample. - [For IT services and consulting firms](https://workwithguava.com/it-services): AI Assessment, AI Rollout, and Ongoing Optimization & Governance; IT services use cases (proposals and SOWs, status reports, documentation, project knowledge) and a sample. - [For tech staffing and recruiting firms](https://workwithguava.com/tech-staffing): AI Assessment, AI Rollout, and Ongoing Optimization & Governance; staffing use cases (screening, job descriptions, submittals, candidate fraud and AI-assisted interview detection) and a sample. - [About Romeo Diaz](https://workwithguava.com/about): the founder's background and how he works. - [Sample AI Assessment](https://workwithguava.com/sample-ai-assessment): illustrative deliverable pages for three fictional firms. - [Main Street Bench](https://workwithguava.com/mainstreetbench): the Main Street Index, which ranks the models tested so far on Main Street Bench at 40% plus four public benchmarks at 15% each (AA-Briefcase, GDPval-AA and AutomationBench-AA from Artificial Analysis, and the Vals Index), with cost per task, a price-performance frontier, and a scorecard for each run. - [MSP Bench](https://workwithguava.com/mspbench): the MSP Index, built the same way on MSP Bench, a private evaluation benchmark of how well AI models look after a managed IT provider, with cost per task, a price-performance frontier, and the spread of each model's runs. - [AI Operations, live](https://workwithguava.com/observability): Romeo's own Codex and Claude Code usage, live from Elastic: model requests, tokens by model, tool calls and response times. Totals only; prompts and responses are never captured. - [Guava Mode](https://workwithguava.com/guava-mode): the free, MIT-licensed guava-mode plugin (https://github.com/romeodiaz/guava-mode), the AI setup Romeo runs Guava on: one AI Context & Skills Hub in the owner's own Notion shared by Claude, ChatGPT and Grok Bot, a model router that sends thinking work to Claude Opus 5.5 and execution to GPT-6.1 Sol, and 23 optional Owner Mode working rules. Guava collects no data from it. - [Privacy](https://workwithguava.com/privacy) and [Terms](https://workwithguava.com/terms).