Delivery capacity, packaged—not another chatbot
Specialist agents operate a controlled engagement workflow: they extract cited requirements, maintain decisions, profile sources, design the model, generate implementation configuration, execute in Fabric and attach evidence to the pull request.
What the accelerator doesthree connected suites, one governed hand-off
Discover
Turns transcripts, questionnaires and emails into a cited requirements catalogue, decision log and human-action queue.
Model
Designs a Fabric Medallion platform, using Kimball dimensional modelling for business-ready Gold data products.
Build & prove
Turns mappings into Delta-Gen assets, runs Fabric, verifies tables and data quality, then opens an evidence-backed pull request.
Where it fitsadopt one stage or the complete delivery model
Discovery
Useful wherever requirements, approvals and decisions are fragmented across people and documents—regardless of target technology.
Greenfield & modernisation
The full accelerator delivers most value where the Fabric architecture, modelling standards and delivery controls can be shaped from the outset.
Brownfield programmes
Modelling or Build can be introduced around an existing estate when mappings, repository conventions and target patterns can be aligned.
What the client keepsdeliverables now, enduring capability afterwards
A working, governed platform
Cited requirements, decisions and source profiles become implementation-ready models and mappings.
- Delta-Gen configuration and repository template
- Tested Fabric tables and data-quality evidence
- Reviewable pull requests and delivery documentation
A platform they can continue to build
Reusable standards and automation help lean client teams add data products consistently without depending on scarce specialists.
- Repeatable delivery process
- Explicit human approvals and ownership
- Version-controlled, auditable evidence trail
Evidence from the reference implementationtransparent proof, including the gaps
Needs a humanthe queue only a person can move
| type | item | engagement |
|---|---|---|
| open question | OQ-001 What is the authoritative business definition of like-for-like sales for the trading pack? | kingsway |
| open question | OQ-002 What exact revenue, margin, and discount definitions should be used so outputs match management accounts? | kingsway |
| open question | OQ-003 What source or business rule should be used to repair the current margin-report failure when clearance lines h | kingsway |
| open question | OQ-004 Should revenue for the pack include or exclude card fees and supplier funding, per Finance's view? | kingsway |
| open question | OQ-005 How should like-for-like treat store closures and refits in addition to the fifty-two-week rule? | kingsway |
| open question | OQ-006 Who owns the product hierarchy: trading or merchandising? | kingsway |
| open question | OQ-007 Should supplier-funded markdown be netted off margin, and what is the exact treatment Finance requires? | kingsway |
| open question | OQ-008 How should the model handle the known orphan store Croydon, which exists in StockRoom but is missing from the | kingsway |
Catalogues being builtlive state per engagement
| engagement | items | draft → confirmed → approved | cited | open Qs |
|---|---|---|---|---|
| Kingsway Retail Group agent-built (run kingsway-2026-07-12-discovery-gpt54) | 109 | draft 109 · confirmed 0 · approved 0 | 100% | 12 |
| Meridian Capital reference catalogue | 24 | draft 5 · confirmed 15 · approved 2 | 100% | 3 |
Agent healthper-stage outcomes across all runs · questionnaire ≈ 84.7s · transcript ≈ 95.2s · email ≈ 96.5s
| stage | ok | failed | success | |
|---|---|---|---|---|
| catalog-maintain | 13 | 1 | 93% | |
| normalize | 14 | 0 | 100% | |
| extract | 14 | 0 | 100% | |
| contradiction-find | 14 | 0 | 100% | |
| decision-track | 13 | 0 | 100% | |
| sync-decision-index | 13 | 0 | 100% | |
| gap-analyse | 13 | 0 | 100% |
Historical regression evidenceJuly test artefacts · not a current-release benchmark
| run | stage score | traps | verdict |
|---|---|---|---|
| kingsway-2026-07-13-build azure_openai · 2026-07-13T13:06 | 100% | 0/0 | star schema verified |
| kingsway-2026-07-12-modelling-from-discovery azure_openai · 2026-07-12T22:34 | 0% | 0/0 | incomplete |
| kingsway-2026-07-12-modelling-golden azure_openai · 2026-07-12T22:33 | 29% | 0/0 | mappings rendered |
| kingsway-2026-07-12-discovery-gpt54 azure_openai · 2026-07-12T22:17 | 0% | 6/6 | diverges |
| kingsway-2026-07-10-gpt54 azure_openai · 2026-07-10T12:26 | 0% | 6/6 | diverges |