AI
RAG and Agent Infrastructure
We design ingestion pipelines, vector search, tool runtimes, secrets, audit logs, quotas, and background workers for AI products that need more than a prototype.
AI Platform Engineering
AI-ready developer platforms for LLM products moving beyond MVP.
ToolLeap builds the infrastructure layer for RAG, agent tools, CI runners, Kubernetes, GPU inference, observability, and enterprise controls so AI teams can ship reliable products faster.
- ◆RAG, agents, runners, and Kubernetes in one roadmap
- ◆Audit, architecture, build, and operate with clear KPIs
- ◆Private deployment, observability, and cost controls
Live radar
Platform status
Capability
RAG, agents, runners, and Kubernetes in one roadmap
Capability
Audit, architecture, build, and operate with clear KPIs
Capability
Private deployment, observability, and cost controls
Status
Reliability score · 99.98%
SLOs met across every service
10dAI infrastructure maturity audit window
4platform stages mapped from MVP to enterprise
1roadmap across product, security, cost, and ops
What we build
Infrastructure for AI products after MVP
ToolLeap helps teams turn experiments into production-grade AI platforms with clear controls for reliability, security, cost, and delivery speed.
CI
Runner and Code Isolation
We turn customer-owned code, CI runners, registries, sandboxes, and private network access into controlled product capabilities.
K8s
Kubernetes and LLM Operations
We build the Kubernetes, GPU inference, observability, routing, and cost-control layer behind reliable AI SaaS and private deployments.
Proof points
Tools behind the platform story
ToolLeap uses real developer tools to show the same engineering patterns we bring to customer platforms: browser runtimes, operational utilities, incident workflows, and automation.
Internal Tool
IP Intelligence
Web console and API that secure platform networks and surface threat intelligence.
Open demo
Internal Tool
WebTerm
Browser-native terminal with granular roles, audit trail, and zero-footprint access.
Open demo
Internal Tool
Incident Brief
Incident radar with reproducible steps, runbooks, and AI-powered summaries.
Discuss this toolApproach
From audit to operating model
We connect infrastructure work to the moment your AI product actually needs it: paid usage, enterprise requirements, tenant isolation, or predictable workloads.
01 · Discovery
Audit the AI platform stage
Map workloads, tenants, model usage, data flows, cost drivers, security gaps, and the business trigger behind the next infrastructure move.
02 · Design
Design the roadmap
Turn RAG, agent tools, runners, Kubernetes, inference, observability, and enterprise controls into a practical sequence of architecture decisions.
03 · Build
Build platform capabilities
Implement the pipelines, control planes, CI isolation, deployment paths, SLOs, and dashboards that make the roadmap usable by product teams.
04 · Run
Operate and evolve
Tune reliability, latency, model routing, tenant margin, and security controls as the AI product moves toward enterprise customers.
Testimonials
Teams trust our product-led DevOps
Platform and engineering leaders share how ToolLeap shaped their rollouts.
“ToolLeap delivered a modular IDP for our fintech stack in record time. Deployment velocity increased without forcing engineers into yet another gated process.”
CTO · GlasWerk Labs (Berlin)
“We finally have a single developer portal, golden paths, and cost dashboards. ToolLeap paired with our platform team and left everything fully documented.”
VP Engineering · Orbiron Energy (Paris)
“Their SRE playbooks and automation reduced incident churn and gave us confidence to expand into new regions.”
CEO · NordicMesh Systems (Amsterdam)
FAQ
Answers to frequent questions
Need something else? Reach out and we will return with an implementation plan within days.
Where does ToolLeap add the most value? +
We help AI and SaaS teams that already moved beyond MVP and now need reliable RAG, agent tools, CI runners, Kubernetes, observability, cost control, or private deployments.
What does the engagement model look like? +
We begin with an AI infrastructure audit, define the roadmap, and build a blended ToolLeap plus customer squad that ships measurable platform capabilities.
Do you replace our DevOps or platform team? +
No. We usually embed with existing engineering teams, add AI infrastructure experience, and leave behind architecture, implementation, dashboards, and operating playbooks.
Ready to scale
Map the next stage of your AI platform
Receive an AI infrastructure maturity scorecard and prioritized roadmap within ten business days.