How is Difinity different from Portkey or LiteLLM?

Portkey and LiteLLM are AI gateways — they route requests between providers, handle load balancing, and optimise costs. They do not detect or redact PII, enforce compliance policies, or generate regulatory audit evidence. Difinity includes all gateway capabilities plus a runtime enforcement layer that applies compliance rules to every request before it reaches any LLM provider. The result is a single platform that handles routing, security, governance, and compliance — rather than a gateway that requires additional tooling to achieve any regulatory compliance.

Can Difinity replace our existing observability tools?

Difinity includes a comprehensive audit trail and observability layer — every AI interaction is logged with full policy context, searchable, filterable, and exportable. For compliance evidence purposes, Difinity's logs are purpose-built for regulatory requirements. However, if your engineering team uses Helicone or Langfuse specifically for prompt version management or LLM performance optimisation, those tools serve a different audience (engineering) than Difinity's compliance-oriented audit trail. Many customers use both — Difinity for governance and compliance evidence, an observability tool for engineering performance work.

Why can't we use AWS Bedrock Guardrails for AI governance?

AWS Bedrock Guardrails only apply to workloads running through AWS Bedrock. If your organisation uses OpenAI, Anthropic directly, or any non-AWS model, Bedrock Guardrails provide no coverage. Additionally, Bedrock Guardrails produce evidence in AWS-specific formats that do not map directly to EU AI Act, ISO 42001, or GDPR requirements — making regulatory reporting significantly more complex. Difinity governs all providers from a single enforcement point and produces compliance evidence in formats that map directly to the regulations you are subject to.

Do we still need a GRC platform if we use Difinity?

Difinity and GRC platforms like Vanta or Drata solve adjacent problems. GRC platforms automate evidence collection for IT security frameworks — SOC 2, ISO 27001, and general data protection. Difinity governs the AI runtime layer — enforcing policies on LLM interactions, detecting PII, and generating AI-specific compliance evidence. Most enterprises with a mature compliance programme will use both: Difinity for AI governance and a GRC tool for broader IT security compliance. They do not duplicate each other.

Is it faster to build AI governance in-house or use Difinity?

A realistic enterprise AI governance build — covering multi-provider routing, PII detection, policy enforcement, compliance dashboards, audit trails, and conformity assessment tooling — takes 12–18 months for an initial deployment. That timeline assumes a team with expertise in AI governance, compliance law, and security engineering, which most engineering teams do not have. Difinity deploys in under 14 days via DNS redirect with zero code changes required. Beyond the initial deployment, every regulation change requires an engineering sprint in a custom build — Difinity handles regulatory updates as part of the platform.

Difinity vs Credo AI — AI Governance Platform Comparison

Difinity vs Credo AI

Credo AI is a Gartner- and Forrester-recognised AI governance platform built around policy management, risk assessment, and compliance documentation. Difinity operates one layer deeper: it enforces those policies at runtime — intercepting every AI request before it reaches the model, redacting PII, and routing traffic intelligently across providers. This page compares the two honestly.

Side-by-Side at a Glance

Capability	Difinity	Credo AI
Runtime Controls
Runtime request interception	✓	✕
PII detection & auto-redaction before model	✓	✕
Secure PII restoration in response	✓	✕
Content evaluation engine (block/allow)	✓	✕
Governance & Policy
EU AI Act policy packs	✓	✓
ISO 42001 alignment	✓	✓
NIST AI RMF alignment	✓	✓
Shadow AI discovery	Partial	✓
Human escalation workflows	✓	Partial
Infrastructure & Providers
Multi-provider API gateway (OpenAI, Anthropic, Gemini, DeepSeek, Grok, Mistral)	✓	✕
BERT-based intelligent routing	✓	✕
Token-level cost management	✓	✕
Cloud, on-prem & hybrid deployment	✓	Partial
Analyst recognition (Gartner / Forrester)	Emerging	✓

Where Credo AI Excels

Credo AI has earned its place in the AI governance market and its analyst recognition is well deserved. For organisations that need a mature, documented governance programme, Credo AI delivers real value.

Policy Governance Depth

Credo AI offers purpose-built policy packs for EU AI Act, ISO 42001, and NIST AI RMF. These are not generic checklists — they are structured frameworks that map regulatory obligations to specific organisational controls and evidence requirements. For compliance teams building out a governance programme from scratch, this is genuinely useful.

Shadow AI Discovery

Credo AI includes tooling to discover unsanctioned AI use across an organisation. Understanding which AI tools employees are using — and documenting them in an inventory — is a prerequisite for any serious governance programme. This is an area where Credo AI has invested meaningfully.

Risk Assessment Frameworks

Credo AI's risk assessment capabilities allow teams to evaluate AI systems against defined criteria before deployment. This pre-deployment assessment layer is valuable for organisations that need to demonstrate due diligence to regulators and auditors.

Analyst Recognition & Market Credibility

Being recognised by both Gartner and Forrester is not trivial. It signals a platform that has passed rigorous evaluation criteria, has a proven customer base, and is supported by a stable vendor. For enterprise procurement teams, this recognition reduces risk in the buying decision.

Where Difinity Differs

Credo AI and Difinity address different layers of the AI governance stack. The distinction is not about quality — it is about where in the AI request lifecycle each platform operates.

Runtime Request Enforcement

Difinity Flow API Gateway

Credo AI governs AI systems at the policy and documentation layer. Difinity sits inline in the request path — every prompt passes through the Difinity Flow gateway before reaching the model. Policies are enforced at the moment of the request, not reviewed after the fact.

PII Redaction & Secure Restoration

Before the model sees anything

Difinity detects and redacts PII from every prompt before it is sent to the LLM provider. The original values are securely re-inserted into the response, so end users receive coherent answers — without sensitive data ever crossing the provider boundary. Credo AI does not operate at this level.

Multi-Provider API Gateway

OpenAI · Anthropic · Gemini · DeepSeek · Grok · Mistral

Difinity acts as a unified gateway across all major LLM providers. BERT-based intelligent routing selects the optimal model for each request based on cost, latency, and policy constraints. Credo AI does not provide an API gateway and cannot intercept or reroute traffic between providers.

Data Sovereignty

Cloud · On-premises · Hybrid

Difinity supports full data sovereignty with cloud, on-premises, and hybrid deployment options. Organisations in regulated industries or jurisdictions with strict data residency requirements can deploy Difinity within their own infrastructure perimeter — ensuring no prompts or responses leave the environment.

Which Should You Choose?

The honest answer is that these platforms are not mutually exclusive — they address different layers of the same problem. The right choice depends on where your organisation's governance gap actually sits.

Choose Credo AI if: your primary need is building a documented AI governance programme — inventorying AI systems, mapping them to regulatory frameworks, generating audit evidence, and getting sign-off from a recognised GRC platform. Credo AI's policy packs and analyst recognition make it well suited for organisations in the early stages of formalising AI governance.

Choose Difinity if: you are deploying AI applications in production and need to enforce policies in real time — blocking non-compliant requests, redacting PII before it reaches the model, managing costs across providers, and maintaining data sovereignty. Difinity's runtime enforcement layer fills the gap that policy governance tools leave open: what happens between the user's prompt and the model's response.

Choose both if: you need a complete AI governance stack. Credo AI's documentation layer paired with Difinity's runtime enforcement layer addresses the full lifecycle — from pre-deployment risk assessment through to real-time production enforcement. Neither platform alone covers everything.