AI isn't magic—it's a data problem. We build the foundations that make AI actually work: grounded in your enterprise data, governed for production use, and designed to deliver measurable value rather than demos that never ship.
"Most AI projects fail not because of the model—but because the data foundation isn't there."
Build retrieval-augmented generation systems that connect LLMs to your enterprise content. Users get accurate, source-backed answers with citations—not hallucinations. We design for access control, traceability, and quality evaluation from day one.
Prepare your data for AI and ML workloads. We build semantic layers, feature stores, and curated datasets that models can actually use—with the data quality, consistency, and documentation that production AI requires.
Implement semantic search infrastructure for similarity matching, recommendations, and RAG retrieval. We configure embedding models, optimize vector indexes, and design hybrid search strategies that balance precision with recall.
Build the infrastructure to deploy, monitor, and manage models in production. We implement model registries, serving endpoints, A/B testing, and the CI/CD pipelines that take models from notebook to production reliably.
Connect large language models to your enterprise systems and workflows. We handle prompt engineering, API integration, response parsing, and the guardrails needed to use LLMs safely in business-critical applications.
Implement frameworks to test, monitor, and improve AI systems over time. We build evaluation pipelines that measure answer quality, detect hallucinations, and track regression as your content and models evolve.
Policies, procedures, onboarding docs—searchable and answerable with source citations.
Field definitions, lineage, "where does this come from?"—for analysts and engineers.
Faster answers for your team, fewer Slack pings, grounded in your actual documentation.
Source-backed responses for support and operations with full audit trails.
If you can point us to the content your teams already rely on—policies, docs, model definitions, tickets—we can design a pilot that demonstrates value fast, without compromising governance. Let's figure out what AI can actually do for your organization.
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