Model
See what depends on what.
Connect your systems, documents and team knowledge. Map who does the work, where it gets stuck and what each change would affect.
Afterflow simulates your business, builds the right AI solution, and learns from every rollout.
Previously at
Our team has delivered production AI and enterprise transformations across Fortune 500 and ASX-listed organisations.
How it works.
Find what works.
Model your workflows, test possible changes and compare their cost, impact and expected return.
Put it to work.
The engine turns the chosen plan into working software. Our engineers support integration, testing and rollout.
Learn from the results.
Compare the forecast with real results. Update your company model before the next decision.
Prototype in a day. Production in weeks.
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Rehearse your next move.
Test what a change could deliver.
Before your business depends on it.
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Simulate
Test thousands of futures.
Compare ways to solve the same problem. Vary adoption, cost and rollout pace to see which plan holds up—and what could change its return.
Build
Turn the plan into software.
The chosen scenario defines the integrations, approval rules and success measures. The engine uses that plan to build the solution, and our engineers test it with your team before it goes live.
Learn
Correct the next forecast.
Compare predicted savings and adoption with the rollout. Use the gaps to correct the assumptions behind the next forecast.
A company that knows how to improve itself.
We’re building a self-improving simulation engine your team can use to discover, test and implement operational improvements.
FAQs.
How is Afterflow different from a consultancy?
Afterflow’s engine keeps learning beyond the project. Every improvement is forecast, measured and fed back into your company model, so each one builds on the last.
What data do we need to get started?
A conversation and a few examples can be enough for an initial assessment. From there, we identify the documents, workflow data and permissions needed for your use case.
How quickly can we get something working?
For a focused use case, we aim for a working prototype in a day and production in weeks. Timing depends on scope, access, integrations and approvals.
What do we actually receive?
A digital twin of your business, a business case with stakeholder approval materials, a working AI solution, and a record of forecast versus actual results after rollout.
How do you handle data security and governance?
We never use your data to train Afterflow without your explicit permission. All accumulated knowledge and learnings stay yours, within your own environment. We work with approved read-only access, record-level permissions and private deployment, including behind your firewall.
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Why not just use ChatGPT or Claude?
Afterflow adds a validated simulation engine and a model of your business. You can test proposed changes against your operating constraints, trace the assumptions and compare the forecast with real results.
How do you measure accuracy?
We test against historical cases and real outcomes. In our historical benchmarks, Afterflow achieved nearly 3× the causal-chain reconstruction score of the frontier models tested. This measures how well it recovered what led to what.
Why should we trust the results?
Every result traces back to evidence, operating rules or clearly labelled assumptions. You can see what supports a conclusion, where the uncertainty lies and what still needs testing.
How do you avoid just fitting past results?
We use regularisation to limit unnecessary complexity in the model. This reduces the risk of memorising quirks in historical data and helps it learn patterns that hold beyond the original examples.
How does Afterflow improve over time?
Each rollout adds evidence about your teams, systems and adoption patterns. The engine uses this to refine its forecasts and identify which initiatives are worth testing next.
Could we build this ourselves?
Yes. Afterflow can help you test whether building your own learning system is the right investment. It connects your assumptions, simulations and actual results, giving your team that system without having to build and maintain it.