fewer catastrophic errors in specialized domains, dropping from ~5% to ~1% vs. strong baselines.
Retrieval engineered for production
Domain-tuned retrieval.Open weights.Your stack.
K² unifies dense, sparse, fusion, and reranker models around the problems your team actually has. Train on your data and deploy open weights inside your infrastructure.
Unified training, consistent runtime
Signals that compound, not compete
Dense, sparse, fusion, and reranker models all learn from the same production queries and hard negatives. That shared loop is why K² keeps recall high, prompt tokens lean, and answers grounded.
Fine-tuning
Train every retrieval signal together
Customer corpus, queries, and hard negatives power shared loops for dense and sparse encoders, the learned fusion model, and the reranker—evaluation feeds new positives and harder negatives back in.
Test-time and generation
Test-time and generation, Fusion and rerankers guard every answer
Dense and sparse retrieval fan out in parallel, the fusion model learns the optimal blend, and the reranker delivers a calibrated verdict before generation—feedback loops route straight into the next tune.
Verified uplifts
Measurable gains where it counts
Precision retrieval translates directly into safer outputs, leaner prompts, and faster agent execution. These are the deltas teams see when Knowledge² powers their RAG stack.
improvement in retrieval accuracy on specialized data compared to leading general-purpose models.
fewer tokens needed for context, reducing LLM costs and improving response times.
Operational cadence
Launch with confidence
We partner closely from data handoff to deployment, ensuring every signal is tuned to your environment and evaluation benchmarks.
Create your domain-tuned model
Launch production-ready AI faster.Upload your corpus (~500-1k pages) and 50-250+ real queries. Our platform initiates the fine-tuning process, training a cohesive family of dense and sparse retrievers, and rerankers, specifically on your data.
Deploy & scale, your way
Deploy in your cloud with guardrails and playbooks.Choose your deployment: call your model via our secure API in the Knowledge² Model Store, or download the open weights for private self-hosting in your AWS, GCP, or Azure VPC. We provide comprehensive guides for seamless integration and scale.
Evaluate & optimize with confidence
Evaluate, monitor, and optimize with live telemetry.We conduct rigorous, shared-budget A/B evaluations against your current RAG stack. Receive a personalized "Which Signals Help Your Data?" report detailing performance deltas, thresholds to enforce, and telemetry hooks to monitor post-launch.
Answers, upfront
Frequently asked questions
Straightforward answers so you can evaluate Knowledge² alongside your current retrieval stack.
Do I need to move my data or change my vector store?
No. You keep your vector store and existing infrastructure. K² delivers open weights for you to host or a secure API endpoint for your model. There is no data migration required.
How much data is needed to get started?
We recommend a starter set of roughly 500-1,000 high-signal documents and 50-250 production queries. More data helps, but we can begin with what you already have and iterate quickly.
How does this impact my LLM costs?
By delivering tighter retrieval and leaner prompts, customers regularly see double-digit reductions in input tokens and a corresponding drop in generation spend.
How quickly can we see the performance improvement?
Teams typically run pilots inside two weeks. Because we evaluate against your existing stack, you get clear deltas before committing to production rollout.
What data telemetry do you collect?
We only capture the evaluation signals you explicitly opt into. When you self-host the models, no runtime telemetry leaves your environment.
Is the juice worth the squeeze? What trade-offs should we expect?
Unified training and learned fusion do ask for a short pilot, but the payoff is immediate: higher recall, calibrated reranker scores, and lower token spend. Teams typically hit positive ROI once the models are serving just a few hundred high-value queries per day.
Launch faster
Ready to ship retrieval your builders can trust?
Bring a corpus, a stack, and the problems keeping you up at night. We will help you tune signals, benchmark improvements, and hand off everything your team needs to run in production.