Three SIs, two internal teams, one programme, and every one of them reporting progress differently. Hapie puts them all on the same gates, the same evidence and the same traceability, in your cloud and your Jira. Your standards are enforced automatically, status comes from artefacts rather than decks, and the knowledge stays when a vendor leaves.
100%
of critical steps carry a named approval and evidence, from every vendor
Up to 60%
rework: defects caught at the gate, not in UAT
60% less
shorter timelines, kickoff to go-live
0
delivery knowledge that leaves with the vendor: playbooks, graph and evidence stay with you
Runs in your cloud and your Jira
Your data never used to train models
Vendors can pay the usage under your mandate
Every vendor brings its own method, its own definition of done and its own status deck. Your architecture standards live in Confluence and get enforced in review meetings, when someone remembers. Quality tracks whichever senior consultant happens to be on the account. And when the engagement ends, the people who understood your estate leave with it. Coding assistants made each vendor's developers faster and changed none of this.
Definition of done
Today:
Encode how your firm delivers into reusable playbooks that run on Hapie, under your brand.
On Hapie:
One evidence gate: deterministic checks, evidence-linked review, second-model review, named approval. Same for everyone
Quality
Today:
Tracks the seniority on the account
On Hapie:
Consistent regardless of who is on the team; the playbook carries the judgement
Your standardsome delivery
Today:
Prose in Confluence, enforced by whoever is in the review
On Hapie:
Rules in the gate. A design that breaks your system-layer standard cannot pass, whichever vendor wrote it
Traceability
Today:
Reconstructed for the audit, incompletely
On Hapie:
Requirement to design to code to test, generated with the work, exportable
Status
Today:
Decks assembled the night before, one format per vendor
On Hapie:
Derived from artefacts and gates passed, comparable across vendors, in one view
When a vendor leaves
Today:
Knowledge leaves with them
On Hapie:
Playbook, context graph and evidence stay in your environment
When every vendor delivers on the same gates, their performance becomes comparable in a way steering meetings never allowed. This is what a programme view looks like with three vendors on Hapie. The numbers are an illustrative example, not a real programme.
Vendor B is not necessarily bad. But for the first time the conversation with Vendor B is about fourteen specific standards violations and a playbook that has only learned twice, not about a red status and a feeling. And the standard being applied is yours.
Why they adopt
Governance, not tooling. Enterprises do not buy another delivery tool; they buy one standard of proof across vendors they already pay, enforced in an environment they already control. That is a procurement and risk purchase, and it is made above the vendor layer.
Why they stay
The standards layer and the ledger. Once an enterprise's standards are encoded and every vendor delivers against them, the evidence ledger becomes the record of the estate. Switching means losing comparability and provenance across every programme since.
How it spreads
The mandate. When an enterprise requires vendors to deliver on its Hapie instance, each new vendor contract brings another SI onto the platform, and each SI carries the method to its other clients. Enterprise demand and SI supply pull each other.
First enterprise programmes are live in the foundation and consumer goods sectors, with instrumented measurement replacing the illustrative figures on this site as data arrives.
Move the sliders to your programme portfolio. The model applies the illustrative ratios on this page to your inputs and shows what changes in effort and governance. It uses percentages, not money; bring real figures to the discovery call.
How to read it.
Rework hours are the share of vendor effort you pay for twice. Review meetings are the governance overhead the gate replaces with evidence. Knowledge retained is what stays with you when the current vendors roll off. the sliders to your programme portfolio. The model applies the illustrative ratios on this page to your inputs and shows what changes in effort and governance. It uses percentages, not money; bring real figures to the discovery call.
Hapie reads your estate before it changes anything: backlog, standards, repositories, live APIs, systems and their relationships. That is why brownfield change and legacy migration are its primary kinds of work, and why impact is known before a design is proposed rather than discovered in UAT.sliders to your programme portfolio. The model applies the illustrative ratios on this page to your inputs and shows what changes in effort and governance. It uses percentages, not money; bring real figures to the discovery call.
It deploys where your vendors already have to work: your cloud account, self-hosted in your network, or air-gapped. Your Jira, Azure DevOps and Confluence stay the systems of record. Your data never leaves the environment you chose and is never used to train models.
Why they adopt
Governance, not tooling. Enterprises do not buy another delivery tool; they buy one standard of proof across vendors they already pay, enforced in an environment they already control. That is a procurement and risk purchase, and it is made above the vendor layer.
Why they stay
The standards layer and the ledger. Once an enterprise's standards are encoded and every vendor delivers against them, the evidence ledger becomes the record of the estate. Switching means losing comparability and provenance across every programme since.
How it spreads
The mandate. When an enterprise requires vendors to deliver on its Hapie instance, each new vendor contract brings another SI onto the platform, and each SI carries the method to its other clients. Enterprise demand and SI supply pull each other.
First enterprise programmes are live in the foundation and consumer goods sectors, with instrumented measurement replacing the illustrative figures on this site as data arrives.
