The platform

A production layer between your data and every decision

Most teams don't have an AI problem — they have a plumbing problem. AuraForge handles ingestion, reasoning, delivery, and governance as one managed layer, so the path from a question to a trustworthy answer is short and observable.

Data Ingestion Engine

Connect databases, warehouses, and APIs. We normalize messy operational data into clean, query-ready structures.

  • Read-only connectors for Postgres, MySQL, S3, and REST APIs
  • Schema inference and type normalization
  • Incremental sync with retry and backfill

LLM Reasoning Pipelines

Retrieval-augmented generation with guardrails, evaluation, and caching so answers stay grounded and cost-controlled.

  • Amazon Bedrock model access with fallback routing
  • Schema-aware SQL generation with validation before execution
  • Response caching keyed on query + data version

Insight & Analytics

Natural-language querying over your own data. Ask a question, get a chart, a number, and the SQL that produced it.

  • Plain-English to validated SQL
  • Auto-selected chart type per result shape
  • Every answer carries its source query

Intelligent Automation

Trigger workflows from model outputs — alerts, reports, and actions that run without a human in the loop.

  • Scheduled and event-driven runs on Lambda
  • Threshold and anomaly triggers
  • Delivery to email, Slack, or webhook

Governance & Security

Row-level access, audit logs, and PII redaction baked in. Your data never leaves boundaries you control.

  • Role-aware access on every query
  • Full audit trail of prompts, SQL, and results
  • Deployed inside your AWS account or ours

Observability

Track latency, cost, and quality of every model call. Know exactly what your AI is doing in production.

  • Per-call latency and token cost
  • Grounding and validation pass rates
  • Alerting on drift and error spikes
Reference architecture

How a question becomes a trusted answer

Every request follows the same governed path. Nothing reaches a model or a database without passing validation, and nothing returns without a citation.

request lifecycle
01 Question received · role & access checked
02 Retrieval — relevant schema + context grounded
03 SQL generated via Bedrock · validated against live schema
04 Query executed read-only · row-level filters applied
05 Answer returned with SQL + source citation
06 Prompt, query, cost, latency logged to observability
See it run

Try a grounded query yourself

The live demo lets you ask questions against a sample operations dataset and watch the SQL and citation appear.

Open the live demo →