Operations Intelligence
Classify incidents, route work and suggest next actions.
Try the Base Open Model now. In a client implementation, TaskSlate connects your approved business data, benchmarks this baseline, customizes the model around your workflow, and deploys the finished AI privately.
Steps 02–05 are completed during your implementation. The public demo lets you test the starting model today.
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This output is a starting point, not a client benchmark. A TaskSlate implementation evaluates both models on approved historical records and held-out test cases before reporting measured results.
Same compact AI architecture. Customized around the way your organization actually operates.
Start with one repeatable workflow where your team needs consistent, structured decisions.
Classify incidents, route work and suggest next actions.
Understand incoming requests and route them using your service rules.
Interpret defects, production events and quality records.
Categorize issues and automate internal service workflows.
Extract and structure information from business documents.
Turn repeatable human decisions into a specialized private AI workflow.
Have a different repetitive workflow?
TaskSlate turns one agreed business workflow into a private AI implementation. We start with your approved business data, benchmark the baseline, customize the model, and deploy the finished system in infrastructure you control.
Read-only, approved access only
One measurable workflow at a time
Built around your workflow and expected outputs
Deployed in infrastructure you control
TaskSlate establishes a measurable baseline before customization. After training, the custom model is evaluated again using held-out client examples that were not used during training.
Evaluate on approved client examples.
Train using business-specific examples.
Measure improvement against the baseline.
Actual results are measured using your approved evaluation dataset.
Deployment and access are designed around the environment and controls agreed for your implementation.
Deploy inside supported client infrastructure.
Restrict database access to approved schemas, tables, views and fields.
Only authorized applications can access model inference.
The deployed model can perform inference privately.
A defined path from a business problem to a supported private deployment.
Workflow mapping
Use-case definition
Success criteria
Data connection
Dataset engineering
Model customization
Benchmarking
Docker deployment
Inference API
Security controls
Evaluation dashboard
Documentation
Knowledge transfer
Deployment support
30-day post-launch support
One defined implementation. No per-token TaskSlate subscription required. Infrastructure and third-party costs, if any, are separate.
TaskSlate adds a private intelligence layer to the business systems you already use.
Show us one repetitive workflow and a sample of how your team handles it today. We’ll assess whether a compact private AI model is a good fit.
Pass along the live demo or start a conversation.