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Machine Learning

Models that inform real decisions, monitored like real software

Forecasting, classification, ranking, recommendation and computer vision, delivered with the pipelines, monitoring and retraining loops that keep accuracy from drifting once the launch excitement fades.

BaselineEvery model is judged against the process it replaces
DriftAccuracy and data-drift alerts wired in before launch
ExplainableFeature importance and evidence behind every score
How we work

AI doesn't fail at ideas. It fails at execution.

Every engagement follows a path from concept to scale with success defined up front, weekly releases and no surprises.

011–2 weeks

Discover

A 60-minute call and a deep-dive sprint that end in a scored opportunity map and a baseline.

021 week

Design

Architecture and stack chosen with a decision matrix and a model bake-off on your data.

034–8 weeks

Build

Weekly releases into your environment with evals, guardrails and traces from sprint one.

042–6 weeks

Scale

Hardening, staged rollout, cost controls and handover so your team runs it.

What every engagement is designed to

BaselineEvery model is judged against the process it replaces
DriftAccuracy and data-drift alerts wired in before launch
ExplainableFeature importance and evidence behind every score
Architecture

Architectures we reach for in Machine Learning & Data Science

Reference patterns we adapt to your constraints. Each links to the full flow, components and trade-offs.

All architectures
Data

Document intelligence pipeline

Unstructured files in, validated records out, humans only on the uncertain ones.

across every level

Hover or tap any part to see what it does. The light shows the order a request moves through.

Gemini / GPT / Claude visionDocument AI / TextractPydantic schemasQueue & review UIERP / LOS APIs
Full architecture
Tech stack

Building on proven, scalable foundations

The strength of any AI system lies in the technology behind it. We choose per workload, benchmark on your data, and build so you can switch.

  • LangGraphMulti-agent workflows
  • LangChain
  • LlamaIndex
  • FastAPI
  • Next.js
  • React
  • PyTorch
  • TensorFlow
  • scikit-learn
  • MCPModel Context Protocol
  • RAGHybrid retrieval + RRF
  • Structured outputsSchema-first AI
FAQ

Get the clarity you deserve

Straight answers to the questions we hear most. Ask us anything else on a call.

No. For many prediction and classification tasks a well-built gradient-boosted model or a small fine-tuned transformer is more accurate, cheaper and easier to explain. We choose per problem and show the comparison.

Let's build intelligent systems that drive growth

Tachyon is the engineering partner for teams that need AI in production, not in a deck. Start with a free 60-minute discovery call.

Contact

Talk to experts about your product idea

Every great partnership begins with a conversation. Whether you are exploring possibilities or ready to scale, tell us what you are actually trying to build.

Prefer to talk?

Pick a 60-minute slot. No pitch, just an engineer with honest answers.

Book a call

NDA available on request. We reply within one business day.