AI-Driven Software Solutions —
Production-Grade From Day One.
We build software where AI is core, not cosmetic. LLM apps, RAG systems, fine-tuned models, predictive analytics — all production-grade from day one.
What we build with AI.
LLM Apps
GPT-4/Claude-powered workflows, agents, assistants
RAG Systems
Semantic search + AI answers over your documents
Predictive Analytics
Forecasting, anomaly detection, churn prediction
Computer Vision
Image analysis, OCR, object detection, quality control
Recommendation Engines
Personalized content, products, next-best actions
AI Automation
Workflow agents that execute multi-step tasks
“We shipped an AI clinical decision tool in 10 weeks. 92% accuracy vs specialist review. Cuts diagnosis time 60%. HIPAA-compliant, on-prem deployment.”
AI-powered software, productionized.
Most AI demos don't survive production contact. We build AI software with eval datasets, guardrails, observability, and fallback paths — so it actually works at scale.
Use case + data audit
Week 1-2Identify highest-ROI AI use case, data inventory, success metrics, baseline benchmarks, risk + compliance assessment.
Prototype + eval
Week 3-5RAG or fine-tuning architecture, 100+ example eval dataset, LLM-as-judge scoring, quality + latency benchmarks locked in writing.
Production integration
Week 6-8API / UI integration, guardrails (output validation, rate limits, PII redaction), observability (Sentry + Langfuse), gradual rollout plan.
Monitor + iterate
Month 3+Performance dashboards, cost monitoring, prompt regression testing, continuous eval against new examples, quarterly model refresh reviews.
AI software, production-grade from day one.
Architecture, evals, guardrails, observability, and fallbacks — all as first-class concerns, not afterthoughts.
Model-agnostic architecture
Provider-abstracted (Claude / GPT / Gemini / open models) so switching is a config change, not a rewrite. Batch API + caching where latency allows.
RAG + structured output
Vector search (Pinecone / Weaviate) grounded in your documents. Zod / Pydantic validation of LLM outputs. Hallucination rates < 3%.
Guardrails + safety
Prompt injection filters, PII redaction (Presidio), rate limits, cost caps per session, moderation via Claude Shield or equivalent abuse detection.
Eval + monitoring
Eval datasets with 100+ real examples, LLM-as-judge scoring, Braintrust / Langfuse dashboards, regression tests on every prompt change.
Built for problems language models solve well.
AI shines at fuzzy-natural-language problems: understanding, summarizing, classifying, generating. For strict-logic problems, conventional code is still better. We'll tell you honestly.
B2B SaaS Products
AI features inside SaaS: summarization, copilot, query-from-natural-language, content generation. Most impactful add-on product layer in years.
Support + Service Teams
Chatbots, ticket triage + routing, response suggestions, knowledge-base search. Typical 50-70% ticket deflection within 90 days.
Analytics + Research
Natural-language data querying, report generation, anomaly detection, document extraction. Data teams become 2-3× more productive.
Creative + Content
Content generation assistants, creative-brief expansion, image-gen workflows. Augment human creative teams, not replace.
Model-agnostic, infra-rich, eval-first.
We run production AI on a deliberately diversified stack — so switching models or providers is a config change, not a rewrite.
WE SERVE YOUR INDUSTRY
Select Your Industry — Get a Custom Strategy
Click your industry below to start your free application — we'll tailor everything to your market.
Financial Services & Insurance
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Healthcare & Life Sciences
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Technology, Software & IT
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Retail & Ecommerce
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Real Estate & Construction
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Hospitality & Travel
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Automotive
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Manufacturing & Industrial
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Education & E-Learning
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Entertainment & Media
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Non-Profit & Government
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Logistics & Transportation
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Ship AI that actually works.
92% accuracy. Production-grade from day one. No AI theater.
AI software pricing.
AI MVP
6 weeks · Proof of concept
AI Product
3-4 months · Production app
Enterprise AI
Private + compliance
AI software, answered honestly.
Which model should I use?
Claude 4.6 for reasoning + long context + code. GPT-5 for general reasoning + tool use. Gemini 2.5 for multimodal + very long docs. Llama 4 for self-hosted compliance. We often run multiple models in one workflow — Claude for reasoning, smaller models for high-volume classification.
How do you prevent hallucinations?
RAG grounds answers in source docs with citations. Structured output validation rejects malformed responses. Eval datasets catch regressions before prompts ship. Three-layer defense gets hallucinations under 3% in production.
Is my data safe?
Yes, architected correctly. We default to enterprise API tiers (Azure OpenAI, AWS Bedrock, Anthropic Enterprise) with zero data retention + no training on your data. PII redacted at the edge.
How much does AI cost to run?
$0.002-$0.03 per user interaction typically. Chatbot at 100K messages / month: $300-$2K in API fees. Cost optimization via prompt caching (Anthropic saves 90% on repeated context), smaller models for easy tasks, batch APIs.
What about EU AI Act?
We classify every AI system we ship under the 4 EU AI Act risk categories. High-risk systems get conformity assessments, model cards, audit trails. Prepared for 2026 enforcement.
Three ways to get started
Pick the path that fits you best — a quick form, a detailed brief, or a live call. Selected service: AI & Automation.
Prefer phone? Call (480) 650-9911 — Mon–Fri · 9am–6pm MST