MCP servers and tool APIs
Standards-based tool servers that expose your systems to any agent — safely and reusably.
AI Engineering
Tooling, MCP & Enterprise Integrations
Agents are only as useful as the tools they can safely use. We build reliable, governed integrations into your stack.
- 275+systems integrated across engagements
- <2 wkstypical time to a new connector
- 100%of integrations permission-aware
Capabilities
Connect AI to everything it needs
Connect AI systems to MCP servers, APIs, CRMs, ERPs and internal tools.
Enterprise connectors
Hardened integrations into CRM, ERP, ITSM, collaboration and data platforms.
Event-driven automation
Webhooks, queues and streams that let AI react to business events in real time.
Legacy system access
APIs wrapped around mainframes, file drops and databases that were never meant for AI.
How it works
The connective tissue of enterprise AI
An agent is only as useful as the systems it can reach. We build the integration layer once — every agent and copilot after that inherits it.
MCP-first
Build a tool once, use it everywhere
We expose your systems as MCP servers — the open standard for AI tool connectivity. Any compliant agent, copilot or IDE can then use them, with authentication and scoping handled centrally.
- MCP servers for your internal APIs and databases
- Central auth, scoping and rate limiting per tool
- Works across Claude, custom agents and AI IDEs
SalesforceSlackSAP
JiraSSnowflake
ServiceNowTeamsDrive
OAuthSSOPermissions-awareReal-time sync
Enterprise-grade
Integrations that survive production
Retries, idempotency, schema validation, circuit breakers and rate-limit handling — the unglamorous engineering that separates a connector that demos from one that runs for years.
- Idempotent writes with validation before commit
- Graceful degradation when downstream systems fail
- Contract tests that catch breaking API changes early
// Route work to the right model const result = await ai.run({ task: "contract_review", context: retriever.fetch(doc), guardrails: ["pii", "grounding"], fallback: "gpt-4.1", });
RESTSDKWebhooksMCP
Real-time
AI that reacts to events, not just prompts
Order placed, ticket filed, threshold crossed — event streams trigger agents the moment something happens, turning AI from a tool you ask into a system that acts.
- Webhook and event-stream ingestion at scale
- Queue-backed processing with dead-letter recovery
- Human-visible action logs for every triggered run
Invoice exception workflowRunning
✓Extract invoice fields1.1s
✓Match against PO0.6s
Resolve mismatch with agentrunning
·Post to ERPqueued
Use cases
Where tooling & integrations delivers value
Agent tool platforms
A governed catalog of tools every internal agent can safely use.
CRM and ERP automation
Salesforce, SAP and NetSuite reads and writes with enterprise controls.
ITSM integration
ServiceNow and Jira workflows driven by AI triage and resolution.
Legacy modernization
Mainframe and file-based systems made AI-accessible without replatforming.
Data platform access
Governed AI queries against warehouses, lakes and operational stores.
Cross-SaaS orchestration
Workflows spanning your collaboration, HR and finance tools.
Delivery
How we build it
We start from the business outcome, then design agents, models, tools and guardrails that can survive production — not just a demo.
- Production-ready architecture
- Secure tool integrations
- Measurable business KPIs
- Operate & improve playbooks
-
1
Discover
Map workflows, data, constraints and ROI.
-
2
Architect
Define models, tools, memory and trust boundaries.
-
3
Build
Ship a production-ready system with evals and observability.
-
4
Scale
Optimize cost, quality and adoption across teams.
The MCP tool catalog changed our velocity. The first agent took a quarter to integrate; the fifth took a week, because every connector was already there, tested and governed.
Works with your stack
Built on the tools you already run
We integrate with your models, clouds, data platforms and enterprise systems — no rip-and-replace.
- MCP
- REST
- GraphQL
- Kafka
- SQS
- Salesforce
- SAP
- ServiceNow
- Workday
- NetSuite
- Snowflake
- Postgres
FAQ
Common questions
What is MCP and why does it matter?
Model Context Protocol is the open standard for connecting AI to tools and data. Build an MCP server for a system once, and every compliant agent or copilot can use it — instead of custom integration per AI project. It's how integration effort stops scaling with agent count.
How do you handle authentication and permissions?
Tools authenticate with scoped service identities or delegated user credentials, so an agent acting for a user can only do what that user could. Secrets live in your vault; every call is logged.
Our core system has no API. Can you still connect it?
Almost always — database-level integration, file exchange, message queues or a thin API wrapper. We've connected mainframes, on-prem ERPs and twenty-year-old line-of-business apps.
Who maintains the integrations after launch?
Your choice: we hand over with runbooks and contract tests, or operate them under a support agreement. Either way, breaking-change detection alerts before things fail silently.
Next step
Wire AI into your real systems
Tell us the three systems your agents need to reach — we'll design the integration layer that gets them there safely.