Research2026-0612 min
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.
ReadAll 4 products on-prem — AI includedOn-premise · Sense ecosystem
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.
4
AI-powered products
7
SDLC stages
40+
tools replaced
100%
on-premise
- Postmancallman
- Jiratasksense
- CopilotOn-Prem LLM
- LinearBdevsense
- BrowserStackcallman
- Trellotasksense
- ChatGPT EnterpriseOn-Prem LLM
- JMetercallman
- Swarmiadevsense
AI inside
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.
0
prompts leaving your network
3×
cheaper than cloud AI subscriptions
100%
inference on your hardware
- On-Prem Eco System LLMAICode review, DORA metrics, security-gap detection, auto-opening tasks and bugs — everything in the SDLC except writing the code.Open
- callmanAIAI reads the code change, picks the regression set to run, and writes tests from your API schema.Open
- tasksenseAIAI turns business text into user stories with acceptance criteria and suggests estimates.Open
- devsenseAIAI flags bottlenecks and review overload before they hit your release date.Open
Who it's for
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.
Banks
Regulated finance
Testing, tasks, communication and the LLM run on the bank's own servers — auditable, and never exposed to an external SaaS.
Government
Sensitive state data
Full on-prem deployment, including air-gapped environments — audit and control stay entirely inside the institution.
Telecom
Subscriber-scale data
Scalable on-prem tooling for teams that already run their own infrastructure — data stays in your data centre.
Products
Four products. One perimeter.
Each product replaces a stack of external tools. Open one for the full breakdown.
- Core of the ecosystemComing soonOn-Prem Eco System LLMOn-premise AI modelThe core of the ecosystem. A model spanning the entire SDLC runs on the enterprise’s own servers — it reviews code, computes DORA metrics, detects security gaps and opens tasks and bugs automatically. The codebase is never sent anywhere.Code review, DORA metrics, security-gap detection, auto-opening tasks and bugs — everything in the SDLC except writing the code.8 toolsOpen
- callmanUnified QA testing platformAI reads the code change, picks the regression set to run, and writes tests from your API schema.24 toolsOpen
- tasksenseProject & task managementAI turns business text into user stories with acceptance criteria and suggests estimates.9 toolsOpen
- devsenseEngineering analyticsAI flags bottlenecks and review overload before they hit your release date.8 toolsOpen
What you get
The numbers we put in the pilot scope.
Internal estimates, confirmed against your own baseline during the pilot — not marketing claims.
3×
faster regression
AI selects the scenarios a change actually touches, instead of re-running the whole suite.
~90%
lower QA tooling cost
One platform instead of 24 separate licences — Postman, BrowserStack, TestRail, JMeter and the rest.
~35%
less time on review & bug triage
AI reviews merge requests, flags security gaps and opens tasks and bugs automatically.
9→1
tools for planning
Jira, Trello, Asana and Confluence boards merge into one platform.
0
data-leak exposure
Test data, API keys, prompts and the codebase never reach an external service.
4–6
weeks to a live pilot
One team, two or three products, success criteria agreed before we start.
SDLC map
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.
- 01Planning & Requirements
- 02Analysis
- 03Design
- 04Development
- 05Test / QA
- 06Deployment / Release
- 07Operations & Monitoring
Insights
Research, articles and product news.
Placeholder entries — replace with your own
Research2026-059 min
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.
ReadArticles2026-067 min
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.
ReadArticles2026-046 min
Migrating from Jira without downtime
A four-week migration plan we run with customer teams, including the rollback path nobody plans for.
ReadNews2026-073 min
callman adds Kafka and Redis assertions to test steps
Message-layer checks now run inside the same scenario as HTTP and database steps.
ReadNews2026-072 min
tasksense ships quarterly roadmap view
Dependencies across epics now render on a single timeline, exportable for steering committees.
Read
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.