Synthetic Minds
Agentic AI Platforms for Regulated Enterprise
AWS-native automation infrastructure with enterprise governance. Built for banking, insurance, and government operations.
Agentic AI Platforms for Regulated Enterprise
AWS-native automation infrastructure with enterprise governance. Built for banking, insurance, and government operations.
Enterprise Agentic Bus platform: governance-first automation infrastructure on AWS Bedrock and SageMaker.
Regulated enterprises in banking, insurance, government, and critical infrastructure.
Shift from AI-assisted to AI-operated workflows while maintaining compliance and governance.
We deliver the foundational platform architecture for enterprise agentic operations, built natively on AWS Bedrock and SageMaker.
The Enterprise Agentic Bus: a governance-first framework for deploying, monitoring, and controlling autonomous AI agents within your infrastructure.
Reference architectures and implementation patterns for Bedrock and SageMaker deployment within your existing AWS environment. IAM, VPC, and security configurations designed for regulated industries.
Operational risk controls, compliance boundaries, audit logging, human-in-the-loop escalation protocols. Built specifically for financial services, insurance, and government.
Hands-on enablement for your enterprise architecture and platform teams. Not training courses. Direct coaching on implementing agentic systems within your operational context.
CIO/CTO-level guidance on AI operating models, organizational transformation, and build vs. partner decisions.
The EAB platform is designed as internal automation infrastructure, not customer-facing AI. This isn't a limitation. It's an architectural decision that reflects where agentic security frameworks actually are today. Public-facing agentic systems introduce risks we won't accept in enterprise deployments. We build for operational reliability in regulated environments, not market demos.
We can walk through the architecture and governance framework for your specific use case.
Schedule a Technical BriefingWe deploy agentic systems exclusively within internal networks. This isn't a limitation. It's an architectural principle.
Agentic systems operate with autonomy, system access, and decision-making authority. They interface with enterprise data, legacy infrastructure, and operational processes. Exposing them to the internet introduces attack surfaces and failure modes we're not willing to accept.
Agentic security frameworks are still immature. We design for operational environments where failure isn't acceptable: banking operations, insurance claims, government services, critical infrastructure. That means internal deployment, network isolation, defense-in-depth architecture.
All agentic systems operate within private networks. No public internet exposure. Full network isolation from external threats.
Built on AWS security foundations: VPC isolation, IAM least-privilege, encryption at rest and in transit, CloudTrail audit logging.
Policy enforcement at the platform layer. Hard-coded operational boundaries. Continuous compliance monitoring. Full audit trails for regulated environments.
Built for environments where operational risk management is critical. Human escalation protocols. Failure-safe designs. Operational resilience by default.
This approach reflects enterprise maturity, not technical conservatism. We build AI systems that operate at machine speed while meeting the governance, security, and risk standards regulated industries actually require.
Most organisations are still using AI for email summaries, document assistance, and meeting notes. Meanwhile, the operational potential sits untapped.
We see the same pattern repeatedly. Boards approve AI initiatives, consulting firms deliver pilots, and everything stalls at chatbot-level applications. The gap isn't technical. It's architectural. You can't bolt AI tools onto legacy systems and expect transformation.
The organisations pulling ahead aren't deploying more copilots. They're rebuilding operational architecture around autonomous, policy-governed systems. They've shifted from AI-assisted to AI-operated workflows.
This shift requires agentic architecture. Autonomous systems operating within defined governance boundaries, interfacing with legacy infrastructure, maintaining full audit trails. Platforms, not point solutions.
Agentic AI systems operate autonomously within governance boundaries. They make decisions, orchestrate workflows, and interface with enterprise systems under continuous policy control.
Copilots assist humans. Agentic systems execute end-to-end processes. Traditional automation follows rigid rules. Agentic systems adapt to context and handle exceptions. The value is operational velocity: systems that run at machine speed while maintaining governance, auditability, and human oversight where it matters.
Complete workflow orchestration across systems, not human-in-the-loop assistance
Hard-coded boundaries, continuous compliance checking, and full audit trails
Orchestration across existing systems without requiring wholesale platform replacement
Built for regulated environments with compliance, security, and operational risk frameworks
Here's where agentic systems deliver real transformation in complex, regulated environments:
Automated orchestration of regulatory reporting, compliance checking, and policy enforcement across business units. Continuous monitoring with exception handling and escalation.
Outcome: Reduce compliance cycle time by 60-80% while maintaining full audit trails and regulatory standards.
End-to-end claims processing, case triage, and decision support. Integration across policy systems, external data sources, and legacy infrastructure with full audit capability.
Outcome: Process routine claims at machine speed with 24/7 operation and 100% audit coverage.
Controlled decision support systems interfacing with enterprise knowledge bases. Policy-governed responses, source attribution, and decision logging for regulated environments.
Outcome: Instant access to enterprise knowledge with complete source traceability and policy compliance.
Cross-system workflow automation for complex operational processes. Exception handling, priority routing, and adaptive scheduling without human intervention.
Outcome: Eliminate manual handoffs and reduce process execution time from days to hours.
Intelligent service desk operations, incident management, and operational triage. Automated diagnosis, routing, and resolution within IT governance frameworks.
Outcome: Resolve Level 1 incidents autonomously with escalation only for complex cases.
Continuous monitoring and autonomous response systems for risk events. Pattern detection, policy enforcement, and escalation workflows across operational risk domains.
Outcome: Real-time risk detection and response with millisecond latency and zero alert fatigue.
We work with enterprise leadership navigating operational AI transformation:
Platform architecture decisions, AWS strategy, build vs. partner trade-offs, and technical operating model design.
AI governance frameworks, operational risk controls, audit requirements, and regulatory compliance in automated systems.
Operational redesign for agentic workflows, change management, and capability building for machine-speed operations.
Strategic AI operating models, competitive positioning, and organisational transformation for the agentic era.
Our work is with regulated enterprises in banking, insurance, government, and critical infrastructure. Organizations where operational risk, compliance, and governance aren't negotiable.
Purpose-built on Bedrock and SageMaker with enterprise-grade security and compliance frameworks.
Deployed in banking, insurance, and government environments with operational risk management expertise.
Platform architecture designed for 24/7 operational environments, not proof-of-concept demos.
Enterprise Agentic Bus (EAB) Architecture
Governance-first framework for autonomous AI operations within regulated infrastructure
For inquiries about the Enterprise Agentic Bus platform, strategic advisory, or technical enablement:
🔒 Your information is handled in accordance with enterprise data protection standards. We'll respond within 24 hours.