Cut the manual work behind your management reports.

The figures are ready, yet your team still documents data models, plans charts and assembles reports. That preparation delays the conversation about what the business should do next. I help finance and data teams scope a sovereign AI assistant for this work: models running on your company's infrastructure, approved inputs and drafts your team reviews. ## Which local model fits the job? My 30 August 2026 comparison used eight small correctness and coding tasks. Scores, alongside median response times from a separate timing test, were: - **Qwen3.8-Flash-Next mixed 4/8-bit: 7/8 tasks; 7.37 seconds.** - **GLM-5.3-Flash Q4 SSD: 7/8; 86.64 seconds.** - **DeepSeek V4 Flash Full-Q4 SSD: 8/8; 202.04 seconds.** The timing test used the same 24,576-character input and 182-character output: three measured requests after warmup, on one workstation. These are configuration-specific test timings. For your company, the implication is practical: choose the model around the task, waiting time and review required. A higher test score came with a longer wait in this comparison. Your workflow decides which balance is useful. ## Turn that evidence into less preparation In a separate local reporting prototype, the assistant inspected a data model and produced a validated report specification covering the requested KPIs, charts and filters. Let's apply that preparation approach to one recurring report. I help define the output, configure the pilot and compare total preparation and review effort with your current process. You get evidence for your investment decision before expanding. [Bring your most time-consuming report. Let's scope the assistant around it.](https://karrenberg.it/?lang=en#contatto)