From your expert’s head to a workflow that runs.
No implementation project. No data science team. Annona connects to what you already have, captures how your best operator actually works, proves it on your own history, and then runs it, with your people approving every action.
3 steps. One clear picture.
Connect your data
Link your ERP, WMS, or operational data source, read-only. No migration, no transformation, no waiting.
- Connects in minutes, not months
- No data duplication required
- Works with existing exports if needed
Annona detects what matters
It analyses your operational patterns and surfaces the signals most likely to become problems, before they do.
- Early signals, not lagging indicators
- Explainable. No black-box outputs
- Tuned to your operational context
You get a clear recommendation
What’s happening, why it matters, and what to do next, with the downstream actions already drafted.
- Situation → Impact → Action format
- Every recommendation is traceable
- Delivered where your team works
A 4-step interview, not a 6-month consulting build.
The moat isn’t the report. It’s the method. Discovery converts tacit expert knowledge into a spec that runs, in 4 structured steps with your domain expert.
Show the output
Your expert shows the finished artefact they produce today: the report, workbook, or decision.
Show the inputs
The systems and data they actually consult, and how the domain objects relate to each other.
Walk one real example
Step by step through a real past case: the rules they follow, the judgement calls, the edge cases.
Review & correct
Annona plays its understanding back; the expert corrects it. Then exception harvest and test cases.
The 11-field workflow spec.
One artefact, three consumers: Discovery captures it, the engine executes it, the product renders it. Below, each field is shown with the real worked instance from our pilot: the supply-availability diagnostic behind SB-4420-K.
A spec isn’t done until it reproduces your expert’s real decisions.
Before any workflow goes live, we replay it against your expert’s real past cases. It must name the same root blockers they did, to a stated pass rate, before a single live commitment.
- Historical replay against real past shortage events
- Target pass rate agreed up front (e.g. ≥90% of cases reproduced)
- The hallucination defence: trust is proven, not claimed
The spec compiles to 2 functions.
diagnose() returns the reasoning trace, verdict and outputs. act() returns the drafted actions. Exceptions, approval gates and test cases govern the guardrails. That’s the whole product surface, which is why it’s auditable.
diagnose(item)
Runs the ordered diagnostic sequence from the spec against live data: reasoning trace → verdict → executive summary + operational workbook → recommended decision.
act(item, decision)
On your approval: system tasks complete automatically; comms to internal teams, suppliers and customers are drafted with rationale and queued for one-click human send.