MCP integrationsPrivate MCP Integrations
A safe, audited bridge between your internal systems and your AI tools — so agents can act on real data without a blank cheque.
Inventory → Scope → Operate
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Custom GenAI Product Features
Generative capability embedded inside your own product, not bolted on beside it.
- Time to value
- 4–8 weeks per feature.
- Deployment
- Hybrid — sensitive steps can stay on-prem
- Category
- Cloud, Integration & AI Infrastructure
The manual version of thisInvictt AI layer
Find the moment
Design for editability
Build for streaming
Control cost
Once it's AI-assisted01/The problem
Your users do not want to leave your app to talk to a chatbot. They want the summarise button, the draft reply, the auto-tag — inside the workflow they are already in, at the moment they need it.
02/How it works
The operating model
What enters, what the system does with it, and what reaches you.
System
Find the moment
We look for the point in your existing flow where a user hesitates or does something tedious. That is where a generated draft is worth something.
System
Design for editability
Generated output is always a draft the user can change. Features that present AI output as final get switched off by users within a month.
System
Build for streaming
Token streaming, optimistic UI and cancellation, so the feature feels immediate even when the model is not.
Check
Control cost
Per-tenant rate limits, caching, and model routing so a single enthusiastic customer cannot reshape your margins.
Read the detail behind each stage
01
Find the moment
We look for the point in your existing flow where a user hesitates or does something tedious. That is where a generated draft is worth something.
02
Design for editability
Generated output is always a draft the user can change. Features that present AI output as final get switched off by users within a month.
03
Build for streaming
Token streaming, optimistic UI and cancellation, so the feature feels immediate even when the model is not.
04
Control cost
Per-tenant rate limits, caching, and model routing so a single enthusiastic customer cannot reshape your margins.
03/What's included
What you actually receive
Concrete deliverables, not a statement of intent.
Feature discovery inside your existing product flow
Streaming UI with cancellation and optimistic states
Editable-draft interaction patterns
Per-tenant rate limiting and cost attribution
Model routing and caching for margin control
Quality evaluation on real user inputs
Built with
- TypeScript
- React
- Streaming APIs
- Redis
- Cost telemetry
Tooling is chosen per engagement. This is what this kind of build typically uses, not a fixed stack we sell.
04/Also in this category
Cloud, Integration & AI Infrastructure
What lets everything above run safely, and keep running.
ConnectSecureScale
MCP integrations
Cloud deploymentCloud-Based AI Deployment
Managed model hosting, frontier API integration, and hybrid architectures that use the cloud where it is the right answer and keep the sensitive parts on-prem where it is not.
Classify the workload → Integrate behind an abstraction → Control cost and exposure
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Content generationAI Content Generation
Text and image production pipelines that hold your brand's voice across real volume.
Encode the voice → Ground the facts → Review
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Is this the problem you have?
Tell us what it looks like at your end. We will say honestly whether this is the right fit — including when it is not.