AI Development
MCP Tooling Integration
We integrate your systems into MCP tooling: build connectors, define schemas, enforce permissions, and make tool execution reliable. Ideal when you already have systems and want to expose them safely to AI clients.
Start Small
Start small in 7 days
Three pilot-friendly options that reduce risk and ship value fast. Choose one, share access, and we deliver a production-ready baseline.
Standard
AI delivery standard
Quality and safety practices we ship with AI builds so the system stays measurable, maintainable, and production-ready.
Logging + tracing
Conversation and tool traces with request IDs, error visibility, and debug-friendly runbooks.
Guardrails + safety
Tool allowlists, PII-safe patterns, refusal behavior, and escalation routes for edge cases.
Evals + regression tests
Golden queries, scorecards, and regression checks so quality improves over time instead of drifting.
Cost + latency controls
Caching, prompt discipline, retrieval tuning, and routing so your app stays fast and predictable at scale.
Documentation + handoff
Architecture notes, environment setup, and next-step roadmap so your team can iterate safely after launch.
Security-first integration
Secrets isolation, role-based access, audit-friendly actions, and minimal data retention by design.
Benefits
What you get
Connect CRMs, ticketing, and internal APIs as tools
Improve reliability with retries and validation
Keep tool access safe with RBAC and allowlists
Reduce one-off glue code with consistent schemas
Make usage traceable with logs and monitoring
Ship tools faster with reusable patterns
Features
What we deliver
Connector development
Connect to internal APIs, databases, and third-party tools with resilient error handling and retries.
Schema and validation
Tool input/output schemas with strict validation to avoid unsafe or inconsistent execution.
Permission enforcement
RBAC checks and policy enforcement so tool access matches your security model.
Safe execution patterns
Allowlists, approvals, and deterministic safeguards for high-impact tool actions.
Observability
Logs and traces for tool usage, errors, and performance so you can operate confidently.
Handoff documentation
Tool catalog, schemas, and runbooks for safe maintenance and extension.
Process
How we work
Discovery
Requirements gathering and planning
Design
UI/UX design and prototyping
Development
Iterative sprints with demos
Launch
Deployment and support
Tech Stack
Technologies we use
Core
Tools
Services
Use Cases
Who this is for
CRM and ticketing tools
Expose safe read/write actions for CRMs and ticketing systems with approvals and logs.
Internal admin actions
Expose controlled internal workflows as tools while enforcing role and permission boundaries.
Read-only data tools
Expose search and lookups safely to AI clients without exposing raw database access.
Tool standardization
Normalize inconsistent internal systems into consistent tool interfaces for agent workflows.
Enterprise adoption
Add governance and monitoring for scalable tool usage across teams.
AI Case Examples
Micro case studies (anonymous)
A few safe examples of outcomes we build for real operations—no client names, just results.
Secure Mobile Solution in Australian Defence Ecosystem
Problem: Secure data workflows were required in a regulated environment with strict access controls.
Solution: Hardened architecture with strict auth, encrypted storage, and audit-friendly engineering patterns.
Outcome: Deployed securely within a regulated ecosystem with clear handoff and operational guidance.
AI Knowledge Base Across 2,000+ Pages
Problem: Teams needed fast answers across long PDFs, but search was slow and results were inconsistent.
Solution: RAG with hybrid retrieval and reranking, plus grounded answers and safer fallback behavior.
Outcome: Reliable answers with <10s response times and measurable improvements on real queries.
Ops Automation with AI + n8n
Problem: Manual approvals and CRM syncing created delays and data inconsistencies across tools.
Solution: Event-driven automation with validation gates and AI-assisted classification where it improved routing.
Outcome: Reduced manual workload significantly with more reliable workflows and operator visibility.
Explore
Related solutions & technologies
Useful next pages if you’re planning an AI pilot or scaling this into a larger product.
Related solutions
Decision Guides
Not sure which to choose?
FAQ
Frequently asked questions
Yes. We design tool catalogs and schemas so multiple connectors can live behind consistent interfaces.
Yes. Approvals are recommended for high-impact writes like refunds, deletions, or permission changes.
Yes. We design versioning strategies so schema changes don’t break clients unexpectedly.
We use proper secrets management, environment isolation, and minimal credential scopes to reduce risk.
Yes. Observability is part of a production MCP integration so failures are visible and actionable.
Yes. We can deploy MCP tooling in your infrastructure with hardened network and access controls.
Related Services
You might also need
Want help with MCP tooling integration?
Share your requirements and we’ll reply with next steps and a clear plan.
Reply within 2 hours. No-pressure consultation.