LLM & Constitutional AI

Large language models give our agents intelligence. Constitutional AI gives them hard conversational boundaries. Together, they deliver conversations that are both brilliant and compliant.

LLMs are powerful but unpredictable

Large language models can generate fluent, contextually relevant responses. But in regulated industries, fluent isn't enough. Every response must be accurate, compliant, and auditable. Uncontrolled LLMs are a liability.

Constitutional constraints, not post-hoc filtering

01

Domain-Tuned Models

We don't use general-purpose LLMs out of the box. Our models are fine-tuned on industry-specific regulatory controls and conversation data. Debt recovery scripts, medical consultations, financial advice scenarios.

02

Constitutional Rules

Regulatory requirements are encoded as constitutional constraints. These are hard rules not breakable prompts the model cannot violate. Not suggestions. Not guidelines. Structural boundaries that shape every output.

03

Multi-Layer Validation

Every LLM output passes through the compliance agent before reaching the caller. Outputs that violate constitutional rules are blocked, reformulated, and re-evaluated. All happening within the latency budget.

04

Grounded Responses

Responses are grounded in retrieved facts including customer records, policy documents, and product data, not generated from memory alone. Reduces hallucination to near zero for factual claims.

05

Continuous Evaluation

Automated evaluation pipelines test model outputs against compliance benchmarks daily. Regression detection catches degradation before it reaches production. Human review for edge cases.

Intelligence with integrity

Industry Constitutions

Pre-built constitutional rule sets for ASIC-regulated financial services, APRA prudential standards, TGA healthcare requirements, ACCC consumer protection, and debt collection guidelines.

Custom Rule Sets

Define your own constitutional rules for internal policies, brand guidelines, and business-specific constraints. Rules are version-controlled and auditable.

RAG Integration

Retrieval-Augmented Generation connects the LLM to your knowledge base, policy documents, and customer data. Responses cite sources. Claims are verifiable.

Hallucination Prevention

Multiple layers of fact-checking, including source attribution, confidence thresholds, and contradiction detection, ensure the model never states something it can't back up.

One Framework

Our constitutional framework works with multiple LLM backends. If there is ever a need to change model. We can do so without rewriting compliance rules. Future-proof against the rapidly evolving LLM landscape.

Explainable Decisions

Every AI decision comes with an explanation trace: which rules were applied, what data was retrieved, and why the response was chosen. Full transparency for regulators and stakeholders.

0
Compliance Gate Coverage
<0%
Hallucination Rate
0
Industry Constitutions
0
Decision Traceability

See constitutional AI in practice

We'll walk you through how our constitutional framework handles your regulatory environment, compliance requirements, and edge cases.