Build the Future of Agentic Intelligence.
The Bitstric Developer Portal provides the infrastructure, models, and research necessary to build, deploy, and scale advanced AI agents.
Developer Tracks
Choose your integration trajectory
Systems Integrators
Comprehensive tools for embedding Bitstric safety sandboxes and models into production environments.
- SDKs (Python, Node.js, Go)
- Deterministic GRC API Reference
- Deployment & Sandbox Guides
Researchers
Dive deep into model architectures, benchmarking methodologies, and core engineering principles.
- Published Papers & PDF Downloads
- Eddy-v1 Sovereign Benchmarks
- Engineering Blog Deep Dives
import bitstric
from bitstric.labs import LabsSafetyClient
# Initialize Bitstric Client & Safety Sandbox
client = bitstric.Client(api_key="BITSTRIC_LABS_KEY")
safety = LabsSafetyClient(endpoint="https://secure-sandbox.cluster.local")
# Audit agent action before execution
response = safety.audit_agent_action(
agent_id="agent-finance-triage",
payload={"action": "export_client_ledger"}
)
print(f"Audit Status: {response.status}, Score: {response.compliance_score}")Latest Release
v2.4.0-stable
Enhanced Context Windows & Audit Exports
Support for up to 128k tokens in core models, plus improved latency for streaming responses.
- • New `/v1/labs/verify-policy` schema
- • Deprecation notice for legacy auth tokens
All Systems Operational
API latency within normal parameters (< 150ms).
WHITEPAPEROCT 2024
Continuous Learning in Multi-Agent Environments
An analysis of failure states and recovery mechanisms when deploying autonomous agents in dynamic systems.