Internal AI Copilot
Loaded- RAG
- Search
- Citations
- Tool calling
Pick a starting point, then adjust the team and hours.
Complexity scales hours, so it moves both cost and timeline. Compressing the schedule trades money for calendar time.
Model architecture, offline/online evaluation design, technical direction.
Feature engineering, training pipelines, experimentation, inference code.
Serving, CI/CD for models, monitoring, drift detection, infrastructure.
Ingestion, warehouse modelling, feature store, data quality contracts.
APIs, integration with your product, auth, queues, storage.
Scope, metric definition, stakeholder alignment, delivery reporting.
Test harnesses, evaluation datasets, regression suites, release gates.
Estimated cost $14,500
310 hours across 5 roles · blended $47/h
Well-understood problem shape. We have shipped this pattern before.
Bands from a focused build to a multi-source one.
Baseline complexity: Standard
Baseline complexity: Complex
Baseline complexity: Complex
The questions we get before a first call.
Hourly rates by role, quoted from a template. Fixed-price is available once discovery is done and scope is frozen.
Most production systems land in 4–16 weeks. The calculator on /pricing gives a range from the same model we use internally.
You do. Full transfer of code, weights, documentation and runbooks.
Least-privilege access, isolated environments, and no training on your data for anyone else. We will work inside your VPC when that is the constraint.