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AI features

Roboticks runs Anthropic Claude on AWS Bedrock behind a small set of typed task definitions. Every AI surface in the product maps to one AITaskType with a fixed model, fixed input/output window, and a fixed token_cost — so plan gating is deterministic and the surface area is auditable.
The customer never picks the model. The backend picks Haiku, Sonnet, or Opus per task. Bills count against the org’s monthly ai_tokens grant; overage stops at the plan ceiling unless the org has a top-up. See Pricing → AI tokens for the unit economics.

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Where AI shows up

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Models and routing

Routing is fixed in app/core/ai_config.py and is not a tunable for customers. The mapping: Bedrock model IDs live alongside the routing table; cross-region inference profiles (us.anthropic...) are baked in.

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How billing works

Each call bills the Bedrock-equivalent token count × 2x margin, with output weighted by the model’s output/input price ratio. So a typical Sonnet request that consumes 5 000 input + 1 000 output tokens at Bedrock prices the customer is charged roughly:
The platform never charges by absolute dollars — it charges in units of ai_tokens the customer’s plan ships with monthly. Top-up packs add ai_tokens_prepaid that never expire. For a worst-case ceiling per task — the figure the plan-gate compares against — see max_billable_tokens() in ai_config.py. The Free plan’s 100 000-token grant covers Haiku-tier tasks but is below the worst-case requirement-generation gate, so the heavy AI features are implicitly Team+.

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What the AI does NOT do

  • It never edits your code, your requirements, your tests, or your evidence packs. Every “AI assist” is a suggestion the engineer accepts or rejects.
  • It never reads your repos directly. AI prompts are built from data already in the platform (test results, requirements text, logs the runner shipped). The hosted MCP server can read more, but only when an LLM calls it through the platform’s billing-and-auth boundary.
  • It never sees a customer’s data outside the Bedrock invocation. Roboticks does not train models. Anthropic does not use Bedrock prompts for training under AWS’s contractual terms.
  • It is not a substitute for the certification auditor. AI assists draft and explain; the engineer signs.

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Plan gating

Customers can buy top-up packs at any tier; topped-up tokens are ai_tokens_prepaid and never reset.

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Next

Test debugging

Triage, flakiness, sim-vs-real, log anomalies.

Requirements & traceability

INCOSE quality, verification, duplicates, gaps, doc chat.

Evidence & standards

Pack narrative, pre-audit Q&A, clause summaries.

Natural-language search

Ask questions; get answers grounded in the project’s data.