Connecting agents to enterprise systems
takes more than software.
Apelogic connects Claude, Codex and custom agents to business systems in compliance-sensitive environments. We handle brownfield complexity and tie commercial terms to production outcomes.
Agents
Vendor-neutral and purpose-built to integrate with existing infrastructure
Systems
Most vendors sell a product. We deliver the outcome.
Gateways and observability suites solve the generic 80%. We handle the rest — agent connected to system, governed end to end, paid only when it works.
Access and permissions
Agents cannot become an all-access backdoor.
Who can access Salesforce, NetSuite, Drive, Slack, or data warehouse through an agent? We map agent access to existing users, roles, permissions, and data boundaries so assistants do not become an all-access backdoor.
Sensitive data and compliance
LLM access changes your compliance posture.
Once customer, financial, or employee data enters an LLM workflow, compliance questions change. We help define what agents can retrieve, expose, summarize, retain, or act on — and what internal policies need to exist around it.
Logging, observability, and auditability
If activity is not reviewable, it is not governable.
Security and compliance teams need to know who asked, what the agent accessed, what data came back, and what action was taken. We design the logging and audit trail needed to make agent activity reviewable.
Architecture and connector choices
Not every connector belongs in production.
MCP servers, native connectors, APIs, gateways, CLIs, and custom integrations all have tradeoffs. We help choose and implement the right path for your systems, security model, and maintenance reality.
Reuse vs rebuild decisions
Most enterprises already have part of the stack.
Most enterprises already have partial investments in API gateways, data platforms, identity systems, and internal tooling. We identify what to reuse, what to wrap, and what to replace before creating another integration layer.
API cost, quotas, and caching
Agent traffic can quietly explode system costs.
Agents can turn occasional API calls into constant system traffic. We plan for rate limits, quotas, caching, intermediate data layers, and cost controls before usage creates surprise bills or brittle workflows.
Get agents connected.Pay when they work in production.
We scope the connector, build it into your existing enterprise stack, and bill against production milestones — not vague consulting hours.
Outcome-based milestones
Fixed pricing tied to production delivery, not open-ended consulting.
Software-agnostic execution
We use the fastest effective path: your existing API gateway, your MCP gateway, Claude MCP SDK, or proven open-source components.
Built for brownfield environments
Works with your existing auth, policy, logging, and security controls.
Price your first connector
Tell us the agent, system, and workflow. Get a starting estimate in minutes.
No sales call required.
Build into your stack
We implement the connector around your existing auth, policy, logging, and security controls.
Operate & maintain
We keep it working as APIs, permissions, agents, and enterprise requirements change.
Connecting Claude to a data warehouse at Helium Mobile
A production connector that turned dashboard-ticket backlog into governed, natural-language analytics self-service.
Helium Mobile's lean data team was a bottleneck — every business question turned into a dashboard ticket. Apelogic connected Claude directly to their Trino data warehouse and built a semantic context layer, so employees get answers in plain English while the data team stays in control of business definitions.
"Apelogic gave our agents safe, governed access to the data warehouse. Employees stopped waiting days for answers."
drop in dashboard data-ops workload
from kickoff to handoff to the Helium Mobile team
semantic context layer, governed by the data team
Dashboard-request bottleneck
- Days-long backlog of dashboard requests
- Data ops translates every business question into SQL
- Superset charts built one ticket at a time
AI-powered data self-service
- Employees ask Claude questions in plain English
- Claude generates SQL on Trino with approved business context
- Useful queries become repeatable Superset charts
- Data team owns the semantic context layer
Team
A small team of builders who’ve started technology companies and operated inside large enterprises — fluent in both startup speed and enterprise complexity.
Co-Founder
Co-Founder
AI Solutions Lead