Generative AI solutions for the enterprise
LLM-powered applications, copilots, and content systems that integrate cleanly with your data, identity, and existing software.
70%
less time on first drafts
writing, summarization, and structured extraction
3x
faster onboarding
copilots embedded in workflows answer in context
<1s
median first-token latency
tuned routing, caching, and model selection
Beyond the demo
An LLM demo is not a product. Production generative AI needs data, evals, controls, and the same engineering rigor as any system you run.
We design and build generative AI products end to end, from model selection and prompt engineering to retrieval, evaluation, and deployment on your cloud of choice.
Generative AI is moving from prototype to production. We help teams cross that gap, building LLM-powered products that integrate with enterprise data, identity, security, and operational realities.
Our work spans model selection, prompt engineering, RAG, fine-tuning, evaluation, and deployment. We design systems where the LLM is one component in a well-engineered application, not a magic black box.
Where teams feel it first
Prototypes that work in a
Prototypes that work in a notebook but fail with real users
Hallucinations and inconsistent answers eroding
Hallucinations and inconsistent answers eroding trust
No way to evaluate or
No way to evaluate or compare model and prompt changes
Unclear cost
Unclear cost, latency, and privacy posture in production
The generative AI stack we build
A connected backbone, not isolated dashboards.
Data and retrieval
Curated corpora, embeddings, vector + keyword retrieval, and grounding with citations.
Models and prompts
Model selection across proprietary and open-source, structured prompts, and routing for cost and quality.
Application layer
API, UX, memory, tools, multi-modal support, and integration with your identity and data systems.
Eval and operations
Golden datasets, quality scoring, drift detection, cost tracking, and prompt versioning in CI.
Our generative AI expertise
Capabilities we ship for this vertical.
LLM application engineering
End-to-end product engineering with LLMs at the core, schema design, retrieval, prompt strategy, tool use, streaming, and graceful degradation when models or APIs misbehave.
- Streaming UIs and partial-response patterns
- Structured outputs and JSON-mode pipelines
- Fallbacks across providers and models
- Rate limiting, quotas, and tenant fairness
Where generative AI delivers
Common use cases we ship
Knowledge assistants
Grounded Q&A over policies, contracts, runbooks, or product documentation with citations.
Document intelligence
Extract, classify, summarize, and route structured information from invoices, contracts, claims, and forms.
Content production
First drafts for marketing, sales enablement, support replies, and internal communications, tuned to brand voice.
Developer copilots
Repo-aware coding assistants for legacy code, internal frameworks, and proprietary stacks.
Business outcomes
What good generative AI delivers
Faster cycle times
Drafting, summarizing, and lookup steps collapse from hours to seconds.
Consistent quality at scale
Tone, structure, and content standards travel with the prompt, not with the person.
Knowledge that flows
Tacit expertise becomes searchable, reviewable, and reusable across teams.
Measurable ROI
Evals and dashboards make it clear which features earn their cost.
Safer, governable AI
Privacy, audit, and policy controls satisfy security and compliance reviews.
Let's build it together.
Generative AI is most useful when it is treated as a system, with data, evaluation, observability, and clear ownership. We help you build LLM products that hold up in production and improve over time.