NeoTek Solutions designs and builds LLM gateway and guardrails architecture for organizations whose AI use is spreading across several teams. An LLM gateway is a central service that sits between your applications and the large language models (LLMs) they use. Every AI request passes through it, so security, cost and quality controls are applied in one place. Guardrails are the checks inside that path that block, redact or flag risky input and output.
When to Use This Architecture
A gateway fits once more than one team or application uses generative AI. Without one, each app handles keys, logging, redaction and cost tracking differently. A gateway gives security and IT teams one control point and one audit trail.
It also fits when you use several models. You may want a low-cost model for simple tasks, a stronger model for complex ones and a private model for sensitive data. The gateway routes each request by policy.
A simpler option can be better early on. A single pilot application may only need the provider’s built-in content filters and standard logging. Plan the gateway before usage spreads, so you do not have to retrofit controls later.
Core Components
Gateway API
We give your applications one internal endpoint to call instead of reaching model providers directly. The gateway authenticates the caller, applies your policies and forwards the request. We keep provider API keys inside the gateway, never in application code.
Model Routing
We write routing rules that pick a model by application, task type, data sensitivity or cost budget. We add failover to a backup model when a provider is unavailable. Your teams can then switch models without changing application code.
PII Detection and Redaction
We detect personally identifiable information (PII) such as names, addresses, account numbers and health details. We mask or replace those values before the prompt leaves your environment. Where your process needs them back, the gateway restores approved values in the response.
Prompt-Injection Defenses
Prompt injection is text that tries to override the system’s instructions, often hidden in documents or user input. The gateway runs classifiers and pattern checks on inputs. It works alongside application-level defenses, such as separating instructions from untrusted content.
Content Filtering
We filter input and output for harmful, off-topic or policy-violating content. Our output checks also look for leaked secrets or sensitive data. Blocked requests return a safe message and create a log entry your security team can review.
Rate Limiting and Cost Controls
We track token usage by application, team and user, since tokens are the small units of text providers bill by. We set quotas, rate limits and budget alerts, so runaway loops and surprise invoices do not reach you.
Caching
A cache stores responses to repeated requests so the model is not called again. Semantic caching matches questions with the same meaning, not just identical text. Caches must respect permissions and expire when the underlying content changes.
Observability and Tracing
We trace each step of a request, from application to gateway to model and back. Your teams can see latency, errors, token counts and which guardrails fired. We use open standards such as OpenTelemetry, so your traces stay portable across tools.
Evaluation
The gateway can sample traffic for automated quality checks and human review. Evaluation sets run whenever a model, prompt or policy changes. This shows whether a change improved or degraded results.
Audit Logs
We log who sent each request, which model answered, what policies applied and what was blocked. We store those logs securely, with retention rules set by your compliance program. We mask sensitive content in logs or restrict who can read it.
How It Works
- An application sends a request to the gateway with its own identity.
- The gateway authenticates the caller and loads the policies for that application.
- Input guardrails scan for PII, prompt injection and disallowed content.
- PII is redacted or the request is blocked, depending on policy.
- The gateway checks the cache and the caller’s quota.
- Routing rules choose a model, and the gateway forwards the request.
- Output guardrails scan the response for harmful content or sensitive data.
- The gateway returns the response and records usage, cost and trace data.
- Sampled requests feed evaluation, and all activity is written to audit logs.
Security, Governance and Guardrails
Access control. Each application gets its own credentials and an approved list of models. Administrators manage policies through change control, not ad hoc edits.
Data protection. Traffic is encrypted in transit, and logs are encrypted at rest. Sensitive workloads route only to enterprise or private deployments. We support business associate agreements with model providers where required, and client data is not used to train public models.
Evaluation. Guardrails are tested too. We check how often they block legitimate requests and how often they miss real risks.
Monitoring. Dashboards show usage, cost, error rates and guardrail activity by application. Alerts flag spikes, repeated blocks or unusual access patterns.
Human oversight. Security and compliance staff review flagged events and adjust policies. Owners of each application review quality reports regularly.
Reference Stack by Cloud
| Component | Microsoft Azure | AWS | Google Cloud |
|---|---|---|---|
| Gateway and API policies | Azure API Management | Amazon API Gateway | Apigee |
| Model access | Azure OpenAI | Amazon Bedrock | Vertex AI |
| Content filtering | Azure AI Content Safety | Amazon Bedrock Guardrails | Vertex AI safety filters |
| PII detection | Azure AI Language PII detection | Amazon Comprehend PII detection | Sensitive Data Protection |
| Caching | Azure Cache for Redis | Amazon ElastiCache | Memorystore |
| Tracing and monitoring | Azure Monitor and Application Insights | Amazon CloudWatch and AWS X-Ray | Cloud Trace and Cloud Monitoring |
| Secrets | Azure Key Vault | AWS Secrets Manager | Secret Manager |
Open-source and on-premises options also fit, including open-source LLM proxies, OpenTelemetry, Redis and Kubernetes. NeoTek Solutions is vendor-neutral and designs the gateway around your platforms and policies.
Common Pitfalls
- Letting teams embed provider API keys directly in applications.
- Logging full prompts with sensitive data and no access restrictions.
- Relying on one guardrail type and assuming it catches everything.
- Setting filters so strict that users route around the system.
- Caching responses without respecting user permissions.
- Tracking cost only at the invoice level instead of by application.
- Changing models without rerunning evaluations.
Where We Apply It
In healthcare, a gateway helps keep protected health information within approved models and logs every access. In financial services and insurance, it supports audit trails, data masking and model governance reviews. In government and public services, it gives agencies a single control point for approved AI use. It also suits any organization that wants one policy layer across many AI projects.
Example scenario: Several departments start AI pilots with different providers. A shared gateway gives them one set of keys, one redaction policy and one cost dashboard.
How Can NeoTek Solutions Help You Put Controls in Place?
A gateway is far easier to add before AI use spreads than to retrofit afterward. We design it around the policies your security team already has.
- What we buildA gateway with model routing, PII redaction, prompt-injection and content filters, quotas, caching, tracing and audit logs around your existing AI applications.
- Built on your policiesWe start from the rules your security and compliance teams already set, then enforce them in one place instead of application by application.
- How we workShort cycles with AI-assisted delivery and human review, guardrail and latency targets agreed early and a working gateway for one application first.
- Skills on the teamCloud and security specialists, AI and machine learning engineers, data engineers and QA in one team, covering routing, redaction, observability and testing.
- What makes us differentOne team covers strategy, build and staffing, so we can hand the gateway to your security team or keep running it with them.
- Evidence for your reviewersApproved-model lists and audit logs give compliance reviewers what they need, though we do not provide legal advice.
Tell us how many AI applications your organization runs today. Book a free AI consultation and we will show you where a gateway would pay off first.
Frequently Asked Questions
What does the gateway you build do?
We build one central service that all your AI requests pass through before reaching a model. It handles authentication, model routing, guardrails, cost limits, caching and logging. That gives your security and IT teams one control point and one audit trail.
What guardrails do you put in?
We build automated checks on the input and output of your AI systems. They redact personal data, block prompt-injection attempts, filter harmful content and hold the assistant to approved topics. We layer them, and we keep your people reviewing what the guardrails flag.
Will the gateway slow our applications down?
It adds some processing time for checks and routing. We keep that overhead small and use caching to make repeated requests faster. We measure latency during testing and agree the targets with you, so you can balance speed and protection.
Can the gateway work with several AI providers?
Yes. We route requests to several commercial providers and to self-hosted open-weight models. Your applications use one interface, so you can switch or add models without rewriting code. We stay vendor-neutral about which models you use.
How does the gateway help our compliance reviews?
We enforce your approved-model list, mask sensitive data and record every request in audit logs. That evidence supports your compliance program and internal reviews. We do not provide legal advice, and your own policies still apply.
Put Controls Around Your AI Use
Tell us which teams use AI today and what worries your security leaders. We will design a gateway and guardrails that fit your policies. Learn more about AI governance, security and compliance or talk to an AI architect.