Production RAG: run evals before you ship to customers
Retrieval quality, citation coverage, and regression suites matter more than model choice. Here is the eval ladder we use before any copilot touches production traffic.
What we build
OpenAI / LLM Integrations — what we deliver
Explore deliverables, tooling, and how we engage. Select any item for detail.
Technology stack
Behind every intelligent solution lies a powerful technology stack
We implement production-grade AI tooling across automation, models, data, and operations—aligned with your cloud standards and compliance requirements.
How we deliver
LLM features in your product—with guardrails built in
We integrate generation, classification, and tool-calling with versioning, budgets, fallbacks, and telemetry your platform team can support long term.
Provider strategy: OpenAI, Azure, Gemini, or private endpoints
Structured outputs, caching, and cost dashboards
Prompt versioning and regression evals
Security review for keys, PII, and retention
Industries
Where embedded LLMs become product advantages
SaaS, fintech, healthcare, and enterprise apps add LLM features when shipping safely matters as much as shipping fast.
Healthcare & Life Sciences
Clinical documentation assist with audit-friendly prompts and de-identification.
Financial Services
Advisor copilots and document summarization with compliance review.
Logistics & Operations
Ops summaries and contract assist with access-controlled retrieval.
SaaS & Tech
AI-native features with per-tenant limits and observability baked in.
Retail & E-commerce
Merchandising copy, search, and support assist with brand guardrails.
Education
Tutoring and content tools grounded in approved curricula.
Public Sector
Policy-aware summarization over internal knowledge bases.
Manufacturing & Industrial
Engineering copilots over specs, logs, and maintenance records.
AI Solutions
LLM integrations we've shipped in production
Product features across summarization, classification, and tool use—with cost controls and safe rollout patterns.
Coin Keeper
Crypto App
CryptoWrex
Ecommerce Banking App
Nostradamus Tips
Smarter Crypto
Social Gold App
Coin Keeper
Nostradamus Tips
Crypto App
Smarter Crypto
CryptoWrex
Social Gold App
Ecommerce Banking App
Process we follow
How we integrate LLMs without production surprises
Architecture review, thin vertical slice, hardening, and operate—with evals before broad feature flags roll out.
Discover & align
Choose models, data flows, and compliance constraints—document threat model and cost envelopes.
Build & evaluate
Ship a narrow feature slice with golden tests and staging parity to production.
Harden for production
Add rate limits, fallbacks, caching, and dashboards for latency, cost, and errors.
Launch & handoff
Hand off runbooks, prompt ownership, and a roadmap for the next LLM capabilities.
Frequently asked questions
Frequently Asked Questions
Common questions about OpenAI, Azure OpenAI, and Gemini integrations.
Still Have Questions?
We’re here to help you!
Yes. We deploy within your VPC or Azure subscription when policy requires it, including private endpoints and key management patterns.
Caching, model routing, prompt compression, per-tenant budgets, and usage dashboards are standard in our integrations.
Golden datasets, regression evals, and feature flags per prompt version before anything reaches all users.
When retrieval and prompting aren't enough we evaluate fine-tuning—but many product features ship faster with RAG and structured outputs first.
We design fallbacks: alternate models, cached responses where appropriate, and graceful degradation—tested in staging before production.
Insights
From our engineering team
Practical notes on architecture, delivery, and shipping software your team can operate—not generic consulting filler.
Designing APIs that survive real-world load
Versioning, idempotency, pagination contracts, and error shapes that keep mobile, partner, and batch clients stable when traffic spikes.
Why CI/CD pays off before you think you need it
Teams delay pipelines until pain is acute. A thin CI/CD spine early reduces rework, makes security reviewable, and keeps MVPs shippable without heroics.