AI & Data Platforms
We build AI features that are grounded in your real data and cite their sources — not a chatbot demo that falls apart on edge cases.
What AI & Data Platforms Means Working With Us
Cited RAG Pipelines
Answers that trace back to an exact page in an exact source document.
AI Matching & Scoring
Parsing unstructured documents into structured criteria for AI scoring.
Brand-Voice AI Agents
Auto-replies and sentiment analysis that stay on-brand across thousands of interactions.
Background Job Processing
Large document batches processed without hitting request timeouts.
Everything That Goes Into a AI & Data Platforms Project
This is the actual scope of work, not a marketing list — every item below comes from real projects we've delivered.
RAG Pipelines With Citations
pgvector-backed retrieval with tuned chunking, so answers trace back to a real source page.
AI Matching & Scoring Engines
Scoring listings, candidates, or documents against structured criteria extracted by AI.
Graph-Based Data Models
Relationship-heavy data modeled as a graph instead of forced into relational joins.
Brand-Voice AI Agents
Auto-reply and sentiment-analysis agents tuned to your brand voice, not a generic tone.
Background Job Infrastructure
Queue-based processing so large batches never hit a request timeout.
Already know what you need?
Skip the back-and-forth — tell us the scope and we'll give you a clear quote and timeline.
What We'll Fix — and What You'll Get Live
If this is already broken
AI Answers You Can’t Verify
Rebuilding retrieval so citations are structural, not a vague model-generated summary.
Pipelines That Fail on Scanned PDFs
Adding OCR fallback for documents that fail silently on native text extraction.
Slow Relationship Queries
Moving from relational joins to graph queries that return in single-digit milliseconds.
Robotic, Off-Brand Auto-Replies
Retuning agent responses on your actual brand voice and past interactions.
Timeouts on Large Batches
Moving synchronous processing to a background queue so nothing silently fails.
What you'll have at the end
AI Users Actually Trust
Visible citations on every answer, not a black-box response you have to double-check.
A Pipeline for Messy Real Documents
Handling scanned images and inconsistent formats, not just clean sample text.
Architecture That Scales
A data model that holds up as your dataset and query complexity grow.
On-Brand AI at Scale
Responses that stay consistent with your brand voice across thousands of interactions.
A Reliable Processing Pipeline
Large batches that process incrementally with visible progress, not silent failures.
Real AI & Data Platforms Projects
Ready to talk about your ai & data platforms project?
Tell us what you're building. We'll tell you what it actually needs.