ENTERPRISE AI
GATEWAY
Give every AI application one governed entry point — centralised model access, policy enforcement, audit trails and cost visibility without slowing delivery.
How we deliver
Prototype-first. We build a working prototype of the core flow in weeks, so you validate the real system before committing to full build — and you own the code.
The Short Answer
What is an enterprise AI gateway?
An enterprise AI gateway is a control plane that sits between your applications and the AI models they call. It centralises authentication, routing, prompt and response policy, data-loss prevention, logging, rate limits and cost tracking, so teams can use multiple model providers without each application rebuilding governance. Solvstrat builds gateways that make AI access consistent, observable and auditable.
Our
Approach
Capabilities
What we build
Unified model access
One API for multiple providers, with routing, fallback and versioning.
See the AI gatewayPolicy & DLP enforcement
Block sensitive data and enforce acceptable-use rules in the request path.
Compliance & trust engineeringAudit & observability
Trace who called which model, with what prompt, cost and outcome.
See governance evidenceCost & quota controls
Per-team budgets, rate limits and model-tier routing to control spend.
See the AI gatewayIdentity-aware access
SSO, RBAC and service identities that match your existing access model.
Identity & access managementEvaluation & guardrails
Response checks, prompt-injection defences and quality monitoring.
AI developmentIs This Solution
Right for You?
Multiple AI Applications
Teams integrating several models without a shared control point.
Regulated AI Use
Organizations that must evidence data handling and access for AI.
Unpredictable AI Spend
Teams with rising model costs and no per-team attribution.
Multi-Provider Estates
Businesses avoiding lock-in by routing across model providers.
What
you'll Gain
Every AI request governed by one control plane — consistent policy, full audit trails, controlled cost and the freedom to use more than one model provider.
01
One Governed Entry Point
Every AI call passes through consistent identity, policy and logging rather than each application rebuilding controls.
02
Auditable AI Use
Prompts, model choices, outcomes and data boundaries are recorded in a form auditors and security teams can inspect.
03
Controlled Cost
Per-team budgets, quotas and model-tier routing keep AI spend visible and predictable.
04
Freedom to Switch Models
Because applications call one API, you can add, replace or fall back between providers without a rewrite.
05
Faster, Safer Delivery
Teams ship AI features without waiting on a separate governance project for every integration.
TOTAL TRANSPARENCY
Common Concerns We Address
We scope the gateway to how your teams actually use AI today, then extend it without turning governance into a bottleneck.
Latency
Policy checks and routing are designed to add milliseconds, with caching and async logging kept off the critical path.
Adoption
Teams keep a simple API and familiar model choices; the gateway removes repeated credential and policy work rather than adding approvals.
Provider Lock-In
The gateway abstracts provider APIs, so models can be added, replaced or failed over without changing application code.
Ownership
You own the source code, deployment and logs, running in your cloud and tenancy under your retention rules.
Proof
AI platforms we’ve built
Governed model access and the controls around it, running in production.
Pricing
Engagement models
Transparent, milestone-based pricing. You own the code, the data and the IP.
01
Fixed-scope milestone
A defined deliverable with milestone-based pricing — best when the scope is clear.
02
Dedicated sprint retainer
Continuous agile delivery with bi-weekly demos — best for evolving products.
03
Fractional CTO / technical leadership
Architecture, security and roadmap ownership without a full-time hire.
Questions
Frequently asked questions
A control plane between your applications and AI models. It centralises authentication, routing, policy, data-loss prevention, logging and cost tracking, so every team uses AI through one governed entry point rather than integrating providers separately.
A traditional API gateway manages HTTP traffic, keys and rate limits. An AI gateway adds model-aware routing, prompt and response policy, token accounting, provider fallback and AI-specific observability — controls a standard API gateway has no concept of.
No. Teams still call a simple API and choose a model; the gateway handles routing, credentials and policy behind it. The goal is to remove repeated governance work from every application team, not to add an approval step to every request.
Yes. The gateway abstracts provider APIs and supports routing, fallback and model-tier selection, so you can use several providers or switch models without rewriting every application.
Yes. You own the source code, the deployment and the logs. It runs in your cloud and tenancy, under your identity and retention policies, with no lock-in to us or a single model provider.
Further reading
Further reading on AI gateways
How we think about governed AI access, routing and the platform underneath it.
What Is an Enterprise AI Gateway?
The five layers of a governed AI entry point, and what each one owns.
Read articleAI Gateway vs API Management
Where traditional API management stops and AI-specific controls begin.
Read articleActive-Active-Active Architecture
When multi-region resilience is worth the operational cost.
Read articleSEE THE PROTOTYPE WE'D BUILD
Give us 30 minutes.
We'll show you the fix.
Tell us where the work slows you down. We'll come back with a prototype of the custom software, internal tools or automation we'd build to remove it — working in weeks, and you own the code.