Four engagements.
One decision infrastructure.
Every Forte engagement produces a named, tangible artifact. Not a deck. Not a set of recommendations. A concrete piece of your decision infrastructure that your team owns, operates, and builds on.
Typical Client Journey
Most clients come to us because they want a Decision Engine. The agents. The Foundation Sprint exists because the agents need a clean place to run.
Building Your Decision Engine
8–20 weeks. The Foundation Sprint, made real.
This is where we build the AI agents that give your leadership team its time back. Agents that synthesize your meetings, draft your weekly reporting, and answer the questions your team used to ask a dashboard. Every agent runs on a clean data foundation we build in tandem, because an agent without a reliable source of truth is just a fast way to get confident wrong answers.
Signature deliverable
The Decision Engine
Your live, operating decision infrastructure. Data flows in. Dashboards update. AI agents surface insights on your canonical data. Leadership makes decisions from a single source of truth.
What you walk away with
- Custom AI agents built for specific jobs in your organization. Meeting synthesis, automated reporting, priority alignment, branded collateral, and more
- The data foundation underneath them. Pipelines, warehouse, and the canonical model that makes the agents reliable
- Dashboards where they still add value. Because sometimes a human just needs to see the number
- Complete documentation and full ownership. No lock-in, no proprietary dependencies
Decision Intelligence Foundation Sprint
6–8 weeks. The most common starting engagement.
Your leadership team gains a clear operating system for decision-making, and the foundation every AI agent needs to be reliable. We define the metrics that matter, design the canonical model of your organization's data, and hand off a blueprint that every dashboard, report, and AI agent will build on.
Signature deliverable
The Decision Data Model
The dimensions, facts, and data dictionary that become the canonical map of your organization. Every downstream investment, dashboards, reporting, AI, pulls from this model.
What you walk away with
- The Decision Data Model (the map, the tables, the dictionary)
- The KPI Framework (the metrics that matter, defined and owned)
- The Dashboard Blueprint (what leadership needs to see, and how)
- A build-ready implementation roadmap
- AI readiness evaluation and governance foundation
AI and Data Health Assessment
2–3 weeks. A diagnostic before you invest.
Before you spend six figures on infrastructure or AI, you should know exactly where you stand. This focused diagnostic evaluates your data maturity, your decision clarity, and your AI readiness, and tells you honestly whether you are ready to build or whether the foundation needs work first.
Signature deliverable
The Decision Readiness Report
A written assessment of your organization's readiness across four dimensions, scored and prioritized, ending in a specific recommendation for what to do next.
What you walk away with
- The Decision Readiness Report
- A prioritized gap analysis (what to fix first, and why)
- Architecture recommendations tailored to your existing stack
- A clear roadmap for getting to decision-ready
Fractional Head of Decision Intelligence
We don't do handoffs. We develop partnerships.
A Decision Engine is not a finished product. It is a living system that needs to evolve as your organization does, and as the AI itself does. Fractional keeps your metrics governed, your dashboards current, and your AI agents sharp. You own the decisions. We own the engine that powers them.
Signature deliverable
The Decision Engine Brief
A monthly written report on your decision engine: status, what we caught, what we shipped, what is emerging in AI that applies to your engine, and the lean-in time available for the month. The watching and tuning is on us. The decisions stay with you. The engine compounds in capability month over month.
What you walk away with (every month)
- The Decision Engine Brief — a monthly written report on engine status, what we shipped, what we are watching, and what is emerging in AI that applies to you
- Continuous tuning of your AI agents — reconfigured as priorities shift, upgraded as models improve
- Ongoing stewardship of your data model and dashboards — kept clean, current, and aligned with your organization
- Up to 2 hours of lean-in time per month — strategic calls, team presentations, or coaching when you want me at the table
Iterative by design
AI is improving in real time, and so is the work we do. Every system we build is designed to be refined. We ship, we watch, we test, we iterate, alongside the tools and alongside our clients. The agent we deploy today is better in six weeks because we are still in the work with you. This is not a handoff. This is a compounding partnership.
Our flagship agent: five hours back every week for one executive leader.
The situation
An executive leader was spending five-plus hours every week doing the same work by hand: reading back through her Zoom transcripts, sifting through email threads, and trying to pull out what actually needed to happen, who needed to do it, and how it connected to her organization's strategic priorities. The information was there. The synthesis was killing her Fridays. And without a consistent system for surfacing commitments, accountability across her team was slipping through the cracks.
What we built
A custom AI agent, built on Claude, that automatically reads her emails and meeting transcripts and produces a weekly brief broken down by team member. Each next step is clearly assigned, with a named owner, and mapped back to the organization's top strategic priorities.
5+ hours
Of executive time reclaimed every week
Clearer accountability
Next steps are visible, owned, and tied to priorities, so fewer commitments disappear between meetings
A decision cadence
That runs on the agent. Her team operates from a shared, synthesized source of truth
How it keeps getting better
This engagement is not a one-time deliverable. As AI capabilities advance, and they are advancing fast, we refine the agent alongside them. New models, new features, new integrations. Each iteration surfaces more time savings, better synthesis, and tighter alignment. It is how we work with every client. Rapid feedback, continuous testing, and a system that compounds in value over time.
Why it worked
This is what an AI agent looks like when it is built right. The agent is not autonomous. It surfaces. The leader decides. And because it queries a canonical set of organizational priorities we defined up front, its recommendations are useful instead of generically plausible. We are still in the work with her, which means the agent gets better every month as Claude gets better, as her team grows, and as her priorities evolve. This is not a product we sold her. It is a system we built with her.
See more agent work we build and are building on our Agents page.
A clear path from assessment to ongoing leadership.
Assess
We evaluate your current data landscape, identify the gaps, and determine your readiness. You leave with the Decision Readiness Report and a clear next step.
Design
We build the canonical map of your organization. The Decision Data Model, the KPI Framework, the Dashboard Blueprint. Leadership sees the shape of its own business, often for the first time.
Build
We implement the Decision Engine. Pipelines, warehouse, dashboards, AI agents. Rigorously tested before anyone touches it.
Evolve
Through fractional leadership, we keep your metrics, dashboards, and agents aligned with where the organization is going, and stay close to the Decision Cadence your team runs.
Where should we start if we are not sure what we need?
Most organizations start with either the AI and Data Health Assessment to get the Decision Readiness Report, or jump directly into the Foundation Sprint if they know they need a Decision Data Model. A 30-minute discovery call is usually enough to recommend the right starting point.
Do you only build AI agents, or do you still build dashboards?
We build both, but we lead with agents. Most leadership teams we work with already have dashboards, or have tried dashboards, and they still cannot get decisions made quickly. Agents are what move the needle. We still build dashboards where they are genuinely the best tool for the job, because sometimes a human just needs to see the number. But the wedge has shifted. Leaders want their time back, not more reports.
Do we need a technical team to work with Forte?
No. Forte is built for organizations without large data or engineering teams. We handle the technical architecture, data infrastructure, and AI implementation. Your team focuses on using the insights to make better decisions.
What size organization is Forte built for?
Our sweet spot is organizations with 50 to 500 employees. Large enough to have real data complexity, but often without dedicated data leadership. We also work with mission-driven organizations and nonprofits.
Do we own everything Forte builds?
Yes, completely. Every dashboard, data pipeline, AI agent, and framework belongs to your organization. No lock-in, no proprietary dependencies, no ongoing licensing of your own infrastructure.
What does "agentic AI" mean in practice?
Agentic AI systems are intelligent assistants that do specific jobs. Synthesizing meetings into action items. Generating audience-specific reporting. Answering the questions your team used to ask a dashboard. At Forte, every agent we build queries your Decision Data Model directly and keeps a human in the loop on decisions that matter, which is why ours are reliable instead of impressive-sounding.
What tools and platforms do you use?
It depends on the organization. We are vendor-agnostic and do not resell software. Our typical toolkit spans modern data warehouses (BigQuery, Snowflake, Postgres), BI and reporting tools (Looker Studio, Power BI, Tableau, Metabase), AI models (Claude, GPT, Gemini, and open-source options like Llama and Mistral when privacy or budget requires it), workflow platforms (Slack, Microsoft Teams, Notion), and whatever CRMs, program systems, and productivity tools the client already uses. We match the stack to the client, not the other way around. A fuller view of how we pick tools lives on the About page.
How is Forte different from a data engineering contractor?
Contractors require detailed requirements and management capacity that most teams don't have. Forte designs the decision infrastructure itself. The Decision Data Model, the governance framework, and the systems that determine what gets built and why. We start with leadership decisions and work backward to the data, not the other way around.
Start with a conversation, not a contract.
A 30-minute discovery call is all it takes to understand where you stand and which engagement makes sense. No pitch, no pressure.