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Runs in your VPC • No lock-in

Ship AI features in
8-12 weeks

Senior pods build and deploy on your stack (AWS/GCP/Azure). Delivery includes code, dashboards, and runbooks.

Best fit: Series A–C, US/EU, 50–300 people, data in Snowflake/BigQuery/Postgres, $30–50k pilot window.

Value Pillars

Ship in weeks, not quarters

Scope: a single use-case with clear inputs/outputs.

Timeline: discovery 1-2 weeks → build 6-10 weeks.

Deliverables: API/SDK, UI hooks (if needed), eval dashboard, handover docs.

Measured outcomes, not hours

Work ties to product/ops metrics: CTR, AOV, conversion, activation, ticket deflection, CSAT.

Acceptance criteria are agreed up front. Demo against them at the end of the pilot.

Reusable components where it helps

Reference patterns for RAG search, recommendations, dynamic pricing, catalog intelligence.

Shorten build time with prebuilt ingestion, retrieval, guardrails, and evaluation pieces.

Your cloud, your rules

Vendor-agnostic architecture.

Encryption in transit/at rest, least-privilege IAM, logs stay in your accounts.

Signature Outcomes

Personalization and Dynamic Pricing

E-commerce / Retail & Marketplaces

Personalization and Dynamic Pricing

Inputs: sessions/events, catalog, orders, inventory, optional competitor feed.

What we ship: embeddings + candidate gen → re-ranker; pricing policy engine with floors/ceilings & audit trail.

Typical metrics to watch: CTR, AOV, revenue lift, price-change acceptance.

In-app LLM Assistant & Product Analytics

SaaS

In-app LLM Assistant & Product Analytics

Inputs: docs/KB, product copy, event stream, ticket history.

What we ship:  grounded RAG with citations & guardrails; experiment dashboards for activation/retention.

Typical metrics: activation rate, task completion time, ticket deflection, CSAT.

LLM Search & Catalog Intelligence

Marketplaces

LLM Search & Catalog Intelligence

Inputs: catalog attributes, seller content, historical edits, search logs.

What we ship: chunking & retrieval tuned for your content; attribute extraction, dedupe, taxonomy assignment.

Typical metrics: conversion rate, zero-result searches, catalog completeness.

How We Work

1

Discovery

1-2 weeks

Use-case selection, KPI and acceptance criteria, reference architecture, access checklist.

2

Build

6–10 weeks

Pipelines/models/APIs, eval harness, basic monitoring, cost guardrails, optional UI hooks.

3

Demo & handover

Run against acceptance criteria; deploy in your VPC; hand over code, dashboards, and runbooks; agree next steps.

Tech Strip

AWS

GCP

Azure · Snowflake

BigQuery

Postgres · PyTorch

scikit-learn · LangChain

LlamaIndex · Pinecone

Weaviate

pgvector · FastAPI

Ray Serve · Airflow

dbt · MLflow

Evidently · Prometheus

Grafana

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smaitic labs

We are an IT Consulting & Software Development Company helping our clients achieve digital transformation to meet varied business needs.

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