Custody
Privacy-first integration
OpenAI and peers supply intelligence; your rows, permissions, and audit trail stay in the database you control.
Engineering · AI products
Custom AI features inside your product
We design and integrate assistants, workflow automation, and AI search into your existing app, with model APIs connected to your roles, business rules, and database.
OpenAI and model APIsData stays in your database
Erratum Solutions builds AI features inside your web or mobile product, using model providers like OpenAI while your system of record stays in your database.
What we build in your product
Assistant
In-app chat
Automation
Your workflows
AI search
Grounded answers
Speech
Production hooks
Staff or customers use AI inside your product, not a separate generic chat tab.
Model reasoning outside. Your data stays home.
Custody
Your database stays home
System of record on your stack; models see scoped context per call
Integration
Inside real products
Features live in apps your team or customers already use
Scope
Built to your spec
Shaped around your workflow, not a generic template with your logo
AI summary
Erratum Solutions builds AI features inside your web or mobile product, using model providers like OpenAI while your system of record stays in your database.
- Erratum Solutions delivers one-off and roadmap AI features for UAE, India, and global clients.
- Typical builds: team knowledge assistants, customer-facing chat, media transcription hooks, and domain-specific prediction or ranking inside an app.
- Providers like OpenAI supply reasoning; your database and APIs stay authoritative, with retrieval and guardrails per request.
- Engagements cover discovery, architecture, integration, staging demos, launch, and tuning from user feedback.
Perspective
Intelligence outside, custody inside
Many vendors sell AI as if you should move your business data into their cloud. We take the opposite default: the model reasons on requests you send, while customers, orders, and records of truth stay in your database.
That means retrieval over your schemas, role-aware tools, and logging you can explain to compliance and operations, not a black-box chatbot pasted onto a login screen.
Requirements vary: a branded assistant for your staff, customer chat grounded in your catalog, speech-to-text in a production tool, or predictors inside a financial app. We scope each build to the product you have and the outcome you need.
Built into your stack
Assistants, semantic search, and automation call your APIs and database rules, not a parallel datastore you cannot audit.
Features your users actually open
Assistants, chat, transcription hooks, or prediction surfaces inside the screens they already use, not a separate tool they forget to visit.
From idea to production feature
Scoped AI shipped inside real apps: planned with your data rules, tested on staging, then tuned after launch.
Three commitments behind every AI engagement
Custody, product fit, and delivery treated as engineering work, not slide deck promises.
Workflows
Product-shaped AI
We design for the job you describe: internal Q&A, storefront guidance, transcription, scoring, or alerts tied to roles and workflows.
Delivery
Ship-ready in your product
The feature ships inside your screens with logging, fallbacks, and iteration from how staff or customers actually use it.
How we ship customized AI solutions
From workflow mapping through model integration, retrieval design, and launch, with demos your team can test on staging before production traffic.
01
Workflow and data mapping
We list which actions need AI, which tables and APIs are authoritative, and what must never leave your network.
02
Architecture and retrieval design
We define RAG sources, tool calls, auth, logging, and fallbacks when a model or provider is unavailable.
03
Integration and hardening
We embed features in your app, rate-limit and monitor usage, and test edge cases with your team on staging.
04
Launch and tune
We go live with monitoring in place, then refine prompts, retrieval, and UX from real usage and your team's feedback.
Frequently asked questions
Do you send our full database to OpenAI?
No. We integrate so each request carries only the context that workflow needs, often via retrieval from your database. Your system of record stays on your infrastructure.
Can you build a one-off AI feature for our existing app?
Yes. That is the core of this practice: a scoped feature inside web or mobile software you already run, or a new module we ship alongside your stack.
Can you add AI to an app we already have?
Yes. We prefer extending existing products with APIs, admin tools, and auth you already trust, rather than forcing a separate platform.
Do you only work with OpenAI?
We commonly work with OpenAI and can integrate other hosted or private models when your security, latency, or cost requirements call for it.
How do you control cost and quality?
We use caching, retrieval limits, evaluation sets, and production monitoring so spend and answer quality stay predictable as usage grows.
Related services
Ready to scope AI inside your product?
Share the workflow, where data lives today, and what good looks like for users. We will reply with fit, boundaries, and a sensible first phase.
Email connect@erratums.com