Explain what went wrong. Enforce what can't ship. Defend every decision. Ship AI that holds up in production, in policy, and under audit.
TrustishowAImovesfromimpressivetodeployable.
Four capabilities. One System of Record. Built for engineers who debug decisions, compliance teams who enforce controls, and leaders who need defensible AI.
See the claims, evidence, assumptions, and tools behind every decision so teams can explain why it happened, debug what broke, and produce a record when it matters.
Set rules at the decision level, not the prompt level. Compliance sets policy without an engineering ticket. Every enforcement is logged as part of the decision record.
When a decision goes wrong, fix it where it happened. Apply the correction in context and carry it into future runs without bouncing between traces, prompts, code, and redeploys.
Ground agent behavior in your organization's knowledge, policies, and trusted sources. Every decision, correction, and approval becomes reusable context that stays with you across LLM models, frameworks, and workflows.
AI Studio captures every decision your team and your agents make, on a graph that remembers.
Every AI decision logged, linked, queryable.
The human interface for trusted AI.
Compounding trust.
Whatever the agent learns is what the human reviews. Whatever the human corrects is what the agent remembers.
Bring visibility, control, and accountability to the AI workflows your teams already run.
Secure coding
An AI coding assistant adds a hardcoded secret to a PR. Your team needs to block it
Outcome
AISquare blocks the merge, attaches the policy, evidence, owner, and suggested fix.
Give teams the visibility and proof they need to move AI from pilot to production.
Explains the decision. Enforces the policy. Remembers the fix. Every run is smarter.
Works with the agents you already built. Add reasoning graphs, policy checks, and decision records without retraining or redeploying.
import aisquare_explainability_sdk as sdk
# Reads EXPLAINABILITY_GATEWAY_URL and EXPLAINABILITY_API_KEY from environment
sdk.init_from_env(service_name="my-agent")
# Run your agent — Agno is auto-instrumented, all spans captured automatically
agent.print_response("...")
# IMPORTANT for short-lived scripts: flush ensures traces reach the gateway
sdk.flush()AISquare works with your team to turn high-value agent workflows into a repeatable system for reasoning, policy, review, and audit.
Bring AISquare into your existing consulting or implementation motion.
Work with our forward-deployed team on your first governed AI workflow.
Use AISquare docs, SDKs, and APIs with your own engineering team.
AI moves fast. Human judgment makes it trustworthy. AISquare connects agents, context, policy, and people so every decision can be understood, guided, and defended.