Stage 1
Request framing
Normalize the user request, identify intent, and determine whether the task is retrieval-heavy, tool-heavy, or both.
Architecture Brief
Kairosys paired LangGraph orchestration with grounded retrieval and permissioned tool use.
The system was designed as an agentic platform, not just a chat wrapper. LangGraph handled the mission runtime and orchestration flow, while retrieval, controlled tools, and structured output contracts kept the system usable in downstream workflows.
System Map
Six layers from intake to report-ready output.
The platform is shaped around control. LangGraph coordinates mission flow, while retrieval, tool use, and output formatting are constrained so the system can be useful without becoming sloppy.
Stage 2
Retrieval strategy
Select the right search path, chunking behavior, and evidence handling before the model begins answering.
Stage 3
Hybrid retrieval
Use dense search, sparse search, and reranking over PostgreSQL and pgvector to improve both recall and passage quality.
Stage 4
Permissioned tools
Route only allowed operations through a governed tool layer with explicit contracts and controlled execution paths.
Stage 5
Structured outputs
Require JSON-shaped answers, stable fields, and citation-aware content so downstream systems can consume the result safely.
Stage 6
Report assembly
Package the result into a usable report artifact rather than leaving the system as a one-off conversational endpoint.
Build notes
The interesting part of this system is not just that it uses agents. It is that LangGraph gives the mission runtime explicit routing and state control, while the agent behavior stays constrained enough to be useful in production-minded workflows.
- LangGraph manages mission routing, state transitions, and ordered execution
- retrieval is grounded and reranked before tool or generation steps depend on it
- tool access is permissioned instead of assumed
- outputs are shaped for machine-readable downstream use, not just human-friendly chat
- report generation turns a workflow into something operational teams can use outside the chat surface
Control Stack
Tool use is governed, not improvised.
The system assumes that agent freedom needs boundaries if the output is going to survive real operating environments.
Grounding
Retrieval quality is a product decision.
Hybrid retrieval and reranking are there to make the generation layer more trustworthy, not to decorate the architecture diagram.
Output Design
The answer is shaped for downstream consumers.
Structured outputs and report packaging push the system toward workflow utility rather than demo theater.
Next Step
If you need this kind of orchestration judgment, use Selected Work as the entry point.
This brief is meant to show how I think about grounded agents, tool control, and report-ready delivery. The next step is a direct conversation about your own workflow and failure modes.