04 — Anticipate

See what’s coming next.

The record of the past is the best guide to the future. We use machine learning and AI to forecast demand, flag risk early, and put your organization’s knowledge to work, with governance that keeps it accurate, fair, and explainable.

  • OutcomeEarlier warning on risk
  • OutcomeForecasts you can plan around
  • OutcomeAI grounded in your data
Sound familiar?

Signs it’s time to call us.

  • 01

    You react to churn, attrition, or cash shortfalls after they happen.

  • 02

    Planning relies on last year’s numbers plus a guess.

  • 03

    You want to use AI, but are not sure your data is ready.

  • 04

    Staff are already using AI tools with no policy or guardrails.

Capabilities

What we deliver.

Engage us for a single capability or combine several. Every engagement is scoped to your goals, your team, and your budget.

  • 04.01

    AI & data readiness

    Assess whether your data, systems, and policies can support AI, and what to fix first.

  • 04.02

    Forecasting

    Demand, revenue, donation, enrollment, and cash-flow forecasts with realistic ranges.

  • 04.03

    Predictive models

    Churn, risk, and propensity models that flag problems and opportunities early.

  • 04.04

    Anomaly detection

    Automatic alerts when key metrics move outside their normal patterns.

  • 04.05

    Generative AI on your data

    Secure assistants that answer questions from your own documents, reports, and data.

  • 04.06

    AI workflow automation

    AI agents for intake, triage, research, and reporting, with humans in the loop.

  • 04.07

    Responsible AI governance

    Use policies, risk reviews, and oversight aligned with frameworks like the NIST AI RMF.

  • 04.08

    Model monitoring

    Track accuracy, bias, drift, and cost so models stay trustworthy over time.

How it works

A clear path from question to result.

  1. 1

    Assess

    Confirm the data, use cases, and guardrails are in place.

  2. 2

    Model

    Build and back-test models against historical data to prove accuracy.

  3. 3

    Deploy

    Put predictions into the tools and decisions where they matter.

  4. 4

    Monitor

    Track accuracy, fairness, drift, and cost, and retrain as needed.

Tailored to you

Same rigor. Different realities.

For nonprofits & foundations

Giving and retention forecasts, program demand planning, early-warning indicators for participants, and responsible AI policies that protect the people you serve.

Nonprofit services
For businesses

Revenue and demand forecasting, churn prediction, lead scoring, anomaly alerts, and AI assistants that put company knowledge at employees’ fingertips.

Business services
Engagement options

Ways to get started.

Pick the model that matches your stage. Many clients start with a fixed-scope engagement and grow from there.

  • Fixed scope

    AI Readiness Assessment

    Evaluate your data and readiness, set guardrails, and prioritize use cases.

  • Project

    Predictive Model Build

    Design, validate, and deploy one high-value forecast or model.

  • Monthly

    AI & Analytics Program

    Ongoing model development, monitoring, and new use cases.

FAQ

Questions, answered.

How much data do we need for predictive analytics?

It depends on the question. Some forecasts work with a few years of monthly figures; others need detailed records. A readiness assessment shows what is feasible now and what to start capturing.

Which AI models and platforms do you use?

We are model-agnostic and work with leading providers such as Anthropic, OpenAI, Google, and Microsoft, along with open-source and classical machine learning tools.

How do you keep AI accurate and fair?

We back-test models before launch, check for bias, keep people in charge of consequential decisions, and monitor performance continuously.

Start here

Ready to talk about AI and predictive analytics?

Tell us the questions you need answered. We will reply personally with an honest view of what your data can reveal and where to start.