Define your AI agent in YAML. TrueNorth runs the conversation — extraction, safety, compliance, WhatsApp delivery.
YAML in. Structured out.
Write your schema once. TrueNorth handles extraction, safety rails, and user interaction automatically.
What makes TrueNorth different
Every feature exists because a production system demanded it.
Hard data.
No synthetic buffer.
Blind automated evaluation across 1,000 real production medical intakes. No cherry-picked runs.
↳ +23.2pp over raw baseline
↳ 8.7× deflection factor
↳ 89% budget reduction
One API.
Any language.
Identical interface across Python, TypeScript, and Go. Drop it into your existing stack in minutes — no framework lock-in, no adapter layer.
from truenorth import Engine, Schema
schema = Schema.load("fitness_plan.yaml")
engine = Engine(schema=schema, model="gpt-4o-mini")
session = engine.create_session(user_id="priya_001")
# Send a message
response = await engine.chat(
session_id=session.id,
message="I'm Priya, I want to lose weight"
)
print(response.message)
# → "Great Priya! How old are you?"Built for real industries
Deployed in the field — not toy demos. Every case study includes completion rates and real numbers.
Rural Medical Intake
Offline sync + Kannada/Hindi support. Collects 12 structured fields without internet, syncs on reconnect. Designed for last-mile health workers.
Read case studyHR Screening
Structured extraction from unstructured candidate responses. Output goes straight to your ATS in JSON — no manual parsing, no copy-paste errors.
Read case studyLead Qualification
WhatsApp Business API integration. Phone number → session mapping → structured lead data. Works across 22 languages with zero extra config.
Read case studyWant to see your industry? These patterns generalise to insurance, education, fintech — anywhere you need structured data from a conversation.
Browse all use casesBuilt in public.
Grown by the community.
TrueNorth is fully open source under Apache 2.0 — built by @amareshhebbar and shaped by every star, fork, and issue. Star the repo to follow progress, or jump in and contribute.
Multi-agent LLM framework — declare outcomes in YAML, skip the orchestration logic. Hallucination firewall, DPDP compliance, WhatsApp native.
Build reliable AI.
Ship faster.
Join the developers building production-grade AI conversation systems with a framework that handles the hard parts.