Ask in plain English, get structured reports

Warestack aggregates and normalizes operational data across your engineering ecosystem — GitHub, Slack, Linear, Jira, and more. You can query everything from pull requests and deployment events to discussion threads, commits, and security rule violations — all in one schema.

Instead of manually digging through each platform, you can write a single prompt like:
"List PRs where files under infra/ were modified and the build failed."
The system will automatically correlate data from multiple sources and return structured, timestamped insights that can be exported or reused in audits.

Warestack's reporting engine uses agentic AI that interprets your prompt, finds relevant data entities (e.g., PRs, commits, reviews), and generates a context-aware analysis. It's not just a chatbot — it combines deterministic SQL-like reasoning with neural summarization, so the outputs are consistent and traceable. For instance, when you ask:

"Show me all PRs that changed authentication code in the past month,"
the system generates an LLM-based summary but also shows you the underlying records, timestamps, and metadata fields. This ensures transparency while giving you concise, human-readable insights.

Yes!

Every LLM-generated report links to the raw JSON event data from the Warestack schema. You can expand it, download it, or even query it with deterministic SQL for cross-checking. This makes it suitable not just for quick insights, but also for audit, compliance, or root-cause analysis where explainability is crucial. In developer terms: every AI-generated summary comes with a reproducible query plan.

You can turn any query or prompt into an automated report. For example:
"Send me every Friday a summary of PRs that touched auth/ or secrets/."
"Alert me if any PR exceeds 500 lines or stays open for more than 48 hours."

Warestack runs these checks continuously and delivers alerts via email or Slack. Scheduling is fully customizable — you define the frequency, filters, and recipients. This means teams can move from reactive monitoring to continuous intelligence, without manual follow-ups or repetitive queries.

All users have access to every feature, agentic checks, reports, and data queries, but within certain data volume and frequency limits based on their plan.

Every Warestack check can be configured to trigger downstream actions when specific behavioral or operational patterns are found. For example, when a rule detects that "PRs larger than 500 LOC took more than 3 days to review," it automatically generates a card and executes the attached actions — like notifying reviewers by email, posting a Slack alert, or creating a Linear comment.