AI across your whole SDLC. Inside your perimeter.
The on-prem ecosystem for regulated software teams. Four products across the full lifecycle for banks, government and telecom — every one running on your own servers, with more functionality than the global tools they replace and their gaps closed.
Every product ships with AI. None of it phones home.
One on-prem model powers all four products. Copilot and ChatGPT are blocked in your environment — this model reviews code, computes DORA metrics, finds security gaps and opens tasks and bugs — where your code already lives.
Built for teams that cannot use the cloud.
Three industries, one constraint: regulated data cannot leave the organisation. Every product is designed around that rule instead of working against it.
Testing, tasks, communication and the LLM run on the bank's own servers — auditable, and never exposed to an external SaaS.
Full on-prem deployment, including air-gapped environments — audit and control stay entirely inside the institution.
Scalable on-prem tooling for teams that already run their own infrastructure — data stays in your data centre.
Four products. One perimeter.
The numbers we put in the pilot scope.
Internal estimates, confirmed against your own baseline during the pilot — not marketing claims.
AI selects the scenarios a change actually touches, instead of re-running the whole suite.
One platform instead of 24 separate licences — Postman, BrowserStack, TestRail, JMeter and the rest.
AI reviews merge requests, flags security gaps and opens tasks and bugs automatically.
Jira, Trello, Asana and Confluence boards merge into one platform.
Test data, API keys, prompts and the codebase never reach an external service.
One team, two or three products, success criteria agreed before we start.
Seven stages, one continuous loop.
From planning to production monitoring, every stage is covered by a product — with the on-prem LLM at the centre, connecting all of them.
Research, articles and product news.
Why regulated teams cannot adopt cloud AI — and what changes on-prem
A field study of 14 banking and public-sector teams, and the three blockers that stop every cloud AI pilot.
Read →Benchmarking on-prem inference on commodity GPUs
What latency and throughput actually look like when the model runs inside the perimeter, not in a hyperscaler region.
Read →Four products, one perimeter: the case for a single SDLC vendor
Tool sprawl is a security surface. What consolidating the lifecycle actually removes — and what it costs.
Read →Migrating from Jira without downtime
A four-week migration plan we run with customer teams, including the rollback path nobody plans for.
Read →callman adds Kafka and Redis assertions to test steps
Message-layer checks now run inside the same scenario as HTTP and database steps.
Read →tasksense ships quarterly roadmap view
Dependencies across epics now render on a single timeline, exportable for steering committees.
Read →The people behind the perimeter.
MeikSense is built hands-on by its founders — from architecture to every customer pilot.
MeikSense grows with the support of ABB Innovation.
Let's plan a pilot inside your perimeter.
A live demo for your team, then a scoped on-prem pilot — usually one team and two or three products.