We explore multiple competing explanations and paths forward.
From proof-of-concept to production deployment. We design, build, and maintain AI solutions tailored to your infrastructure, team, and business objectives.
We're engineers and ML practitioners who've shipped AI systems at scale. We partner with your team to design, build, and deploy solutions that integrate with your existing infrastructure and deliver measurable results.
Internal tools, automation workflows, and copilot interfaces built on OpenAI, Anthropic, or open-source models.
Purpose-built models for classification, extraction, prediction, and domain-specific use cases.
Intelligent document processing, data extraction, and end-to-end business process automation.
Pipelines, vector databases, and storage systems optimized for ML workloads and real-time inference.
On-premise, cloud, or hybrid deployments. We work with your security requirements and existing stack.
Labeling, annotation, cleaning, and dataset design for training high-quality models.
We take AI projects from concept to production. Our team handles architecture design, model selection, integration, testing, and deployment—working alongside your engineers to ensure knowledge transfer and long-term maintainability.
class ProductionPipeline:
def __init__(self, config):
self.model = load_model(config)
self.vector_store = init_store()
self.metrics = MetricsCollector()
async def process(self, input):
embeddings = await self.embed(input)
context = self.vector_store.query(
embeddings, top_k=5
)
response = await self.model.generate(
input, context=context
)
self.metrics.log(response)
return responseQuality data is the foundation of every successful ML project. We provide end-to-end data services—from annotation and labeling to cleaning and validation—ensuring your models train on accurate, well-structured datasets.
Every engagement follows a proven methodology that de-risks AI projects and ensures alignment between business objectives and technical implementation.
We start by understanding your business context, existing infrastructure, and success criteria. This phase includes stakeholder interviews, data audits, and technical feasibility analysis.
We develop a working prototype using iterative sprints. This includes model selection, training, integration with your systems, and continuous validation against your success metrics.
Production deployment with comprehensive testing, monitoring setup, and rollback procedures. We work with your ops team to ensure smooth handoff and operational readiness.
Post-launch support and optimization. We analyze production data, fine-tune models, and expand capabilities based on real-world usage patterns and evolving requirements.
Document processing, risk assessment, fraud detection, and regulatory compliance automation.
Clinical documentation, medical coding, patient communication, and operational efficiency.
Demand forecasting, route optimization, inventory management, and exception handling.
Contract analysis, due diligence automation, regulatory monitoring, and document review.
Product copilots, search & discovery, content generation, and intelligent automation.
Knowledge management, proposal automation, client intelligence, and research acceleration.
We're practitioners, not consultants who hand off a strategy deck. Our team writes production code, deploys infrastructure, and stays engaged through launch and beyond. Every project includes working software.
AI solutions don't exist in a vacuum. We design for your existing stack, security requirements, and operational constraints. On-prem GPU clusters, air-gapped networks, multi-cloud—we've built for all of them.
Our team includes ML engineers, infrastructure specialists, and domain experts who've shipped AI at scale. We don't rely on boilerplate solutions—we architect systems specific to your use case.
Not every problem needs AI. We'll tell you if a rules-based system, third-party API, or simpler approach is the right answer. Our goal is your outcome, not maximizing project scope.
We work alongside your team, not in a black box. Documentation, training sessions, and pair programming ensure your organization can maintain and extend what we build.
Most clients work with us across multiple projects. We offer ongoing support, model monitoring, and optimization to ensure your AI systems continue delivering value as your business evolves.
A mid-market insurance firm needed to automate claims document extraction and routing. We built a custom pipeline combining OCR, LLM extraction, and business rule validation—deployed on their existing AWS infrastructure.
— VP of Operations, Regional Insurance Provider
Let's discuss your AI implementation needs. We'll assess feasibility, outline a technical approach, and give you an honest evaluation of timeline and investment.
Or email us directly at developers@alternativehypothesis.ai