Engineering
Autonomous software lifecycle support with strong governance and release quality control.
99.9%
Uptime metric
- • Full-stack PR reviews
- • Bug triage and root cause
- • Legacy refactoring
All Pages
Deploy LLMs and AI agents on your own infrastructure. Full data sovereignty, OpenAI-compatible APIs, zero vendor lock-in.
72h
First internal pilot
0
Vendor lock-in
24/7
Observability

Security posture
Audit-ready by design
Enterprises switching from public API providers to private AI infrastructure see measurable cost and efficiency gains within the first quarter.
73%
Lower inference cost
Compared to OpenAI / Anthropic API pricing at enterprise volume
12,000+
Engineering hours saved per year
Through autonomous agent workflows replacing manual processes
4.2×
Faster time-to-production
From POC to production with pre-configured orchestration stacks
€0
Per-token cost after deployment
Run unlimited inference on your own GPU infrastructure
From foundational models to production-grade agent systems — built for teams who refuse to depend on third-party APIs.
Deploy and operate private large language models, vision models, speech-to-text and image generation — all on your infrastructure.
Build multi-agent workflows with function calling, retrieval-augmented generation and shared memory across agent instances.
Adapt models to your domain with LoRA fine-tuning, RLHF, or train small-to-mid-range models from scratch on proprietary data.
Precision-tuned agent modules ready for immediate integration into your enterprise stack.
Autonomous software lifecycle support with strong governance and release quality control.
99.9%
Uptime metric
Workflow automation and resource steering for predictable execution.
Sub-2s
Response time
Campaign generation and segmentation loops driven by live signal intelligence.
+140%
ROAS uplift
Autonomous outreach and pipeline acceleration with intent-aware sequencing.
82%
Meeting book rate
Global infrastructure health and security telemetry in one operational surface.
12ms
Latency
A unified orchestration layer lets specialized agents coordinate through shared context and policy controls.
AGENT
One specialized agent handles a complete task end-to-end. Ideal for focused workflows like document analysis or code review.
See how owning your AI stack compares to renting from third-party providers.
| Capability | Public API (OpenAI, etc.) | NexPatch Private AI |
|---|---|---|
| Data sovereignty | Data sent to external servers | 100% on your infrastructure |
| Cost at scale | $0.03–0.06 per 1K tokens | Fixed GPU cost, unlimited tokens |
| Model customization | Limited fine-tuning options | Full LoRA, RLHF, custom training |
| Agent orchestration | Basic function calling | Multi-agent, supervisor, RAG |
| Vendor lock-in | High — proprietary APIs | Zero — open-source models |
| Compliance | Shared infrastructure | GDPR, EU AI Act ready |
| Latency control | Variable, provider-dependent | P99 < 200ms on-premise |
We ship in short cycles so your teams can validate impact quickly while staying compliant and production-safe.
Infrastructure & access baseline
Model deployment and orchestration
RAG, guardrails and policy controls
Monitoring, handover and SLA operations
Combine Private AI with our other products for maximum impact.

We co-build and co-found digital products. From MVP to market — backend, frontend, infrastructure, and go-to-market.

AI-native data intelligence and pipeline orchestration with visual workflows, enterprise operations, and forecasting intelligence.
Your models and data remain in controlled infrastructure with policy enforcement and auditable access boundaries.
We integrate with existing tools via OpenAI-compatible interfaces and stage rollout by business-critical use case.
We baseline operating cost and value per workflow so leadership can validate impact before broad rollout.
Whether you need a full-stack product, private AI infrastructure, or predictive analytics — we're ready to build it with you.
See Private Agent Systems in action
Book a 30-minute live demo with our engineering team