Before adopting Akashic, agree what goes live

Platform evaluations have a way of turning into tours. Data flows in, charts appear, a conversational answer looks impressive and everyone nods. At the end, the sponsor still doesn’t have what they actually need: evidence that the organisation can use this configured service for a real decision, with clear responsibilities and a cost they can live with.

We’d rather you finished an Akashic evaluation with that evidence than with a good impression. Here’s how we suggest getting there.

Start with one bounded decision

Pick a real use case with edges. A monthly customer profitability review built on approved finance and operational sources is a good illustration. Name the person who will accept the result, the owner of each source and the users allowed to see the evidence. Now the evaluation has a business boundary instead of a feature list.

Agree exactly what’s in scope

The Akashic platform page describes seven modules: Data Pipelines, Master Data, Data Warehouse, Business Intelligence, Ask Akashic, Machine Learning and Governance. Each covers a different part of the journey from source records to decisions. Your evaluation should show how the parts your question needs work together. It doesn’t need to demonstrate every feature we have.

AI agents are in preview. Give preview work its own acceptance boundary, and don’t let it become an unstated dependency of a production commitment. Ask us to name the exact release, the modules enabled and the integrations supported for your environment. A blog post is not a release notice.

Then test what the use case relies on. For a cited answer, inspect the records and definitions behind it. For entity resolution, look at the hard matches and how they’re reviewed. For Business Intelligence, trace a measure back to its agreed calculation.

Draw the deployment boundary clearly

Akashic runs in the cloud, on premises or as a hybrid. The real decision is more specific than a hosting label: where data is stored and processed, where model inference runs, who administers the environment and who responds when something goes wrong.

Map the information path for your configuration, including connectors, logs, backups and model providers. Note who can access each part and which controls govern that access. Then have your own security and legal owners assess the actual arrangement against your requirements.

The National Cyber Security Centre’s cloud security principles ask good questions about administration, operational security, user management and evidence. Use them to agree who is responsible for what. They aren’t a certification claim about Akashic, and they don’t replace a review of your deployment.

Run an acceptance exercise with hard cases

Prepare a handful of business questions, each with expected evidence and a named reviewer. Include a missing source, a conflicting record, an out-of-date document and a user who lacks access. Agree in advance what a correct refusal, or an honest “unresolved”, looks like.

Run it against the configured environment and keep everything: outputs, source references, reviewer decisions. Resolve unexplained differences before widening the audience. A great answer to a prepared demo question is useful. Your acceptance exercise should also look like the questions people will bring on an ordinary Tuesday.

Agree how changes are handled. A new source, a different model or a revised definition may mean rerunning part of the exercise. Decide who approves those changes and how users hear about anything material.

Accept the operating service, not just the software

Before rollout, confirm how sources will be maintained, how users get support, how escalation works and what handover material exists. Include the recurring costs and the work that stays with you. A delivery partner can carry agreed responsibilities, but the engagement should spell out who owns what.

Decide what evidence you’ll need before expanding. The next business unit may bring different permissions, identities and quality requirements. Treat the first release as the pattern and the next one as a fresh decision.