Production-grade AI integration into real business systems — from intelligent automation and enterprise search to AI-powered workflows and analytics. We move teams past the demo — LLM features, RAG pipelines, and workflow automation inside the products you already run, with evals, guardrails, and cost controls baked in from day one.
Production-grade AI integration into real business systems — from intelligent automation and enterprise search to AI-powered workflows and analytics.
Applications launched across industries since 2015.
Clients worldwide — most stay long past the first launch.
Four disciplines anchored to the same production standards — from first prototype to live rollout.
Conversational systems across customer support, operations, onboarding, internal tools, and enterprise workflows — context-aware, multilingual, and grounded on your data.
etrieval-augmented generation over your wikis, SOPs, PDFs, CRMs, and operational knowledge — turned into searchable, citable AI answers with role-based access control.
Email processing, AI document intelligence, approval flows, summarization pipelines, and CRM automations — orchestrated end-to-end with proper guardrails.
Executive summaries, AI-generated reports, operational dashboards, and forecasting assistance — turning raw operational data into decisions your team can act on.
A handful of failure modes break what should be a clean production rollout. Each one is preventable — and every one is on our day-one checklist.
of enterprise pilots never reach production — most fail on evaluation, observability or cost governance, not on model quality.
Industry consensus · Gartner, McKinsey
Teams ship features on vibes and screenshots. When the model drifts or a vendor swaps, no one knows it broke.
Every project ships with a versioned eval suite — pass thresholds gate every deploy. Drift is caught in CI, not production.
Generic embeddings, no reranking, no citations. The output sounds confident and is confidently wrong.
Hybrid (BM25 + vector + rerank) retrieval, citation-mandatory prompts, and ground-truth evaluation on every change.
Prompts drift in version-controlled chaos. Small wording shifts break downstream behaviour with no audit trail.
Every prompt is versioned, evaluated and A/B tested. Roll-backs in one command, with an audit trail for every change.
Latency spikes, regressions and cost overruns stay invisible until the invoice. No way to debug a bad response.
Per-request traces, token spend, latency and eval scores — with alerts on regression before your users notice.
A single chatty endpoint blows the budget. No per-tenant caps, no caching layer, no forecast.
Per-tenant cost caps, prompt & response caching, and model routing — cheap models first, smart models on escalation.
PII leaks through prompts. No DLP, no audit log, no compliance story when procurement starts asking.
PII filters on input and output, a full audit log, and deployment options for SOC 2 / HIPAA / GDPR contexts.
A repeatable engineering rhythm — every engagement runs on the same playbook, so you know what each week looks like before we start.
We identify high-value AI opportunities and assess operational readiness, data quality, workflow complexity, and integration feasibility — before committing a single line of code.
Retrieval strategy, data pipelines, security architecture, evaluation systems, observability, and governance models are defined up front, so nothing important is discovered mid-build.
A production-focused vertical slice is deployed in your environment and benchmarked against operational metrics: latency, cost, usability, retrieval quality, and business impact.
Prompt governance, guardrails, monitoring, access control, auditability, rate limiting, and rollback systems get wired in before any real traffic touches the system.
Staged rollout, A/B testing, prompt optimization, retrieval improvements, model updates, and ongoing performance monitoring — AI systems evolve continuously, and so does our support.
Five operating rules that keep engagements on-spec, on-time, and on-budget — backed by transparent reporting your finance team can audit.
A redacted example of the weekly report every active client receives — same format regardless of engagement size.
Every phase ships with a written scope and a fixed price. Scope changes pause work and trigger a written change order — never a surprise invoice.
We pause at 90% of the cap and check in. You decide whether to continue, descope, or wrap — no $30k overrun emails the week after a sprint closes.
Every Friday you receive a one-page report: hours, spend, what shipped, what is next. Reconciles to the invoice line-by-line.
You pay for engineers who can ship — no padded teams of juniors learning on your budget. Average tenure across our delivery team is 6+ years.
Right-sized infra, autoscaling, model selection, response caching. Your monthly cloud and LLM bills get reviewed every sprint, not at end-of-quarter.
Three production deployments with the architecture and outcomes our clients consented to share. Named clients available on request.
Support teams spending excessive time manually summarizing tickets and conversations. Integrated LLM-powered summarization directly into the support workflow with editable summaries.
Operational teams struggling with mass document retrieval across large document repositories. Built OCR, indexing, and contextual retrieval into a single auditable platform.
Manual creation of thousands of eCommerce product descriptions across multiple languages. Built an AI catalog-generation pipeline integrated into the product management system.
Six sectors where we have delivered measurable outcomes — each with its own regulatory shape, data realities, and operational pace.
AI workflow automation, patient systems, and operational intelligence — built for HIPAA-grade workflows.
AI catalog systems, AI support, recommendations, and multilingual content — tuned against real conversion targets.
AI copilots, embedded AI workflows, and intelligent analytics — inside the products your customers already use.
AI reporting, operational dashboards, and workflow automation — for ops teams that move physical or digital goods.
AI content workflows, metadata generation, and search intelligence — for catalogs that live or die by discovery.
Internal AI systems, AI knowledge management, and operational automation — for teams of hundreds, not handfuls.
A modern, battle-tested stack spanning cloud, backend, frontend, and mobile — chosen to ship secure, scalable products faster.
Wordpress
Yii
Vue
Vercel
TypeScript
Supabase
Redis
React NativeReact
Python
PostgreSQL
PHP
Node.js
Nginx
Next Js
MySQL
MongoDB
Meteor
Laravel
Kubernetes
IOS
Hybrid
GitHub Actions
GCP
Firebase
Express,js
AWS
Angular
Azure
DockerPick the one that matches where you are. Not sure? Talk to us — we'll recommend based on your goals, timeline, and risk appetite.
Stuck projects, unclear ROI, expensive demos. We map your surface area, score readiness, and write a no-fluff plan.
End-to-end: from prototype to production-grade integration. Testing, observability and cost controls wired in from day one.
A senior squad inside your team. Continuous iteration, maintenance, upgrades, and feature delivery.
Send a short brief — what you're trying to ship, where you're stuck, what's worked and what hasn't. We'll come back within one business day with an architecture sketch and an honest read.
