Intelligence should not be a privilege.
For too long, the organizations with the deepest data capabilities have been the ones with the biggest budgets. Forte was built to change that.
Built by people who lived the problem.
Forte was founded on a simple observation: organizations of all sizes are drowning in data and starving for insight. Not because the data is bad, but because the infrastructure to use it has always been too expensive, too technical, or too slow to build.
We spent years watching talented teams spend more time wrangling spreadsheets than making decisions. We watched executives fly blind through quarters that their own data could have predicted. We decided there was a better way.
Forte exists to give every organization, regardless of size or technical resources, the data intelligence that used to require a full data science team to achieve. That is what we mean when we say democratized.
Four principles that shape how we work.
Clarity over complexity
We believe the best solution is the one your team will actually use. We build for the person making the decision, not the person who built the model.
Outcomes over outputs
We do not measure success by dashboards delivered or models deployed. We measure it by the decisions your organization makes better because of them.
Access over exclusivity
Data intelligence should not require a Fortune 100 budget. We price, package, and build for organizations at every stage.
Trust through transparency
You own your data, your models, and your infrastructure. We build it. We hand it over. No lock-in, no black boxes.
How we build.
The right stack depends on the organization. A 50-person nonprofit with a limited budget does not need the same infrastructure as a 400-person services firm with a mature data team. Matching the tooling to the client is part of the work.
We are deliberately vendor-agnostic. We do not resell software, we do not take commissions, and we do not push any specific platform. What we do is meet clients where they are, build on what they already pay for when it makes sense, and recommend alternatives when it does not. Every engagement ends with the client owning the work, free to run it, modify it, or migrate it without us.
Our typical toolkit spans the following categories. We mix and match depending on the client's size, budget, existing stack, and strategy.
Data warehousing and storage
BigQuery, Snowflake, Postgres, and other modern databases depending on scale and what the client already uses. For smaller organizations, a well-structured Postgres instance or BigQuery project often beats a more expensive enterprise warehouse. For larger organizations with existing investments, we integrate rather than replace.
Dashboards, reporting, and BI
Looker Studio, Power BI, Tableau, Metabase, and similar tools. For smaller organizations already on Google Workspace, Looker Studio is usually the simplest path. For organizations on Microsoft 365, Power BI is often the natural fit. For clients with dedicated analysts or more complex reporting needs, Tableau or Looker hold up. We pick the tool that matches the team that will actually use it, not the one with the fanciest demos.
AI and language models
Our default is Claude (Anthropic API) for agent reasoning and synthesis tasks. We also build with GPT models when the client is already invested in OpenAI, and Gemini when the team lives in Google Workspace. For budget-constrained or privacy-sensitive clients, we work with open-source models including Llama (Meta), Mistral, and Qwen, running locally or on a private cloud instance. The model choice is a strategy decision as much as a pricing one.
Agent orchestration and workflow
LangGraph, Claude's native tool use, CrewAI, and direct API orchestration for simpler builds. For most engagements at our scale, simpler patterns beat framework-heavy ones. We only reach for full agent frameworks when the complexity genuinely requires them.
Workflow, messaging, and collaboration
Slack for team communication and agent notifications. Microsoft Teams when the client lives there instead. We build agents that post directly into existing channels rather than forcing leaders into a new interface.
Productivity and knowledge work
Google Workspace (Gmail, Calendar, Drive, Docs, Sheets) and Microsoft 365 (Outlook, OneDrive, SharePoint, Word, Excel). Notion, Asana, Monday, and ClickUp for project and knowledge management. Zoom and Google Meet for meeting transcripts that feed our Synthesis Agent pattern.
Data pipelines and integration
Fivetran, Airbyte, or custom connectors depending on the scale and sensitivity of the data. dbt for transformation when the client has a real warehouse. Simpler ETL patterns when they do not.
CRMs and operational systems
Salesforce, HubSpot, Bloomerang, DonorPerfect, Apricot, CaseWorthy, PowerSchool, Infinite Campus, and whatever else the client already uses. We build on top of existing systems rather than asking clients to rip and replace.
The goal is never to sell a stack. The goal is to build decision infrastructure the client can actually operate, with tools that match their size, their budget, and where they are going. We meet clients where they are. We do not force a proprietary stack.