For Private Companies

Engineering for companies shipping AI, data and software.

We build and repair production systems: AI and LLM features, machine learning, data platforms, cloud infrastructure and full-stack applications. We are led by Bo Peng, who holds an M.S. in Data Science from Indiana University and seven cloud certifications across AWS, Azure and GCP, ranks in the top 200 of more than 200,000 competitors on Kaggle, and has client-facing delivery experience across five consulting firms including Guidehouse and NTT DATA.

Start here, at no cost

Send us the thing that is not working. You get a written answer in one business day.

Not a discovery call. Not a deck. Send the actual artifact and we will read it: the query plan, the serving config, the cloud bill, the schema, the retrieval pipeline, the security questionnaire your buyer sent back, the scope document you are about to sign. You get back a short written note naming the two or three things we would change and why.

Most of the time that note is the whole answer and you go and do it yourself. When it is not, you already know how we think before anyone talks about money.

contact@precisionfederal.com

Six places we do the most good

Most of the work arrives the same way: something already exists, it works in a demo, and it is failing under real traffic, real documents, real customers or a real bill.

AI and LLM systems in production

Retrieval that holds up on real documents, agents that do not wander, evaluation you can defend, and inference costs you can actually explain line by line.

Retrieval and RAGAgent orchestrationEvaluation harnessesInference cost work

Machine learning and data science

Forecasting, ranking, classification, anomaly detection. Models measured under held-out evaluation and distribution shift, not on the training set.

ForecastingRanking and searchChurn and riskComputer vision

Data platforms and analytics

Pipelines that do not break at 3am, a modeling layer people agree on, and numbers the business can act on without a data team of twelve.

Ingestion and ELTWarehouse modelingMetrics layerData quality

Cloud and infrastructure

AWS, Azure and GCP. Right-sizing, multi-region when it is genuinely needed, disaster recovery you have actually tested, and a bill that stops climbing.

Cost reductionKubernetes and GPUsIaC and CI/CDObservability

Full-stack product engineering

The API, the admin panel, the background jobs, the frontend that stays fast when the table has a million rows. The unglamorous parts that decide whether a product survives.

APIs and backendsAdmin surfacesQueues and jobsFrontend performance

Security your buyer will accept

SSO, role-based access, audit logs, tenant isolation, data-residency guarantees you can keep. Built to survive the review, not to describe one.

SSO and RBACAudit loggingTenant isolationDeployment into a customer VPC

When the blocker is not your code. It is your buyer's security review.

A deal is agreed. Then the questionnaire arrives, or the architecture diagram gets sent to someone in security, and the answer comes back that the data cannot leave their environment, or cannot be processed where you process it, or cannot be seen by your staff at all. Engineering did nothing wrong. The product simply was not designed for a buyer with that constraint, and now a signed-in-principle contract is sitting still.

Most engineering firms can build your product. Far fewer can tell you what your buyer's reviewer is actually going to object to, and what the smallest change is that removes the objection.

This is the work we do most often and it is the reason companies come to us specifically. Single-tenant and customer-VPC deployment. Data-residency guarantees that survive contact with an auditor. Zero-retention architectures. Telemetry that is safe by construction. Support models for a customer whose data you are not permitted to see. Data-flow maps that answer the question a reviewer is really asking instead of the one on the form.

We answer the hard version of these questions in writing, with the reasoning shown, so your team can take the answer to the buyer without us in the room.

  • Read the questionnaire or the reviewer's objection and say plainly what it means
  • Name the smallest architectural change that removes it
  • Say which promises you can keep and which ones will fail an audit later
  • Write it down in language your buyer's security team accepts

Three shapes, and you can stop after any of them

ShapeWhat happensWhat you get
Written second opinionYou email the artifact. We read it and answer.A short written note within one business day. No charge.
ReviewOne to three weeks on a specific question: an architecture, a cost line, a system you are about to buy or rebuild.A written report with findings ranked by what they cost you, and the reasoning behind each one. Fixed fee, quoted before we start.
BuildWe do the engineering, against written acceptance criteria agreed up front.Running software, the code, and the documentation to keep it running without us. Fixed fee or a defined monthly engagement.

We work by email and in writing. It suits this kind of work: the answer is a document you can forward to your board, your buyer or your own engineers, and it is still there in six months when somebody asks why the system is built that way.

Send us the thing that is not working.

The query plan, the bill, the config, the questionnaire, the scope you are about to sign. A written answer in one business day, no charge and no meeting.

contact@precisionfederal.com