Full-Process Digitalization
From sample intake to signed reports — registration, task dispatch, testing, review and e-signature, all online.
Digital Solutions for Testing & Inspection Laboratories
Purpose-built for disease control, food, environmental and third-party testing laboratories — standardize workflows, digitize records and automate reporting to meet ISO 17025 / CNAS requirements.
WHY YIHENG
From sample intake to signed reports — registration, task dispatch, testing, review and e-signature, all online.
Automatic data capture from GC, LC, AAS and other major instruments, with complete raw spectra retained.
ISO 17025 / CNAS-ready workflows, full audit trails and data integrity (ALCOA+) support.
Private and localized deployment keeps your data inside your network. Certified at China MLPS Level 3.
A Laboratory Information Management System (LIMS) is the software layer that carries a sample from acceptance to report. In testing and inspection organizations, it replaces paper worksheets and spreadsheets with traceable electronic records, enforces review and approval steps, and keeps raw instrument data linked to the sample that produced it.
Yiheng LIMS is built for Chinese testing and inspection organizations: disease control centers, food and drug inspection institutes, environmental monitoring stations, and third-party testing companies. It supports the workflow patterns these labs actually run — sampling plans, parallel microbiology and chemistry tasks, quality control samples, and report issuance under review.
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Contact UsA LIMS implementation is less about installing software than about writing down how the laboratory already works and making the system follow it. We start with the standards each laboratory tests against, the review and approval chain, and the way samples and retention are handled. Those decisions become configuration: task templates, review levels, report layouts and retention rules.
The next stage is a pilot. One section, one or two test categories, real samples but a controlled volume. The point of the pilot is not to prove the software runs; it is to find the points where the laboratory's written procedure and its actual practice disagree. Those gaps are what derail projects later, and they are cheapest to fix early.
Only after the pilot do we migrate historical data and switch the remaining sections. Training happens at the moment people start using the system for real work, not weeks in advance, because a training session before go-live is quickly forgotten.
Feature lists are a poor way to compare laboratory systems; most of them look similar on paper. The differences that matter show up later, in four places.
First, record integrity: once a result is entered, can it be altered without a trace? Second, offline operation: can sampling staff work where there is no network, and does that data merge cleanly afterwards? Third, instrument coverage: how many of your instruments can feed results in automatically, and what happens with the rest? Fourth, migration: can your existing records be brought across so the audit trail stays continuous?
A vendor that answers these four questions concretely, with reference sites and a pilot plan, is usually a better bet than one that answers with a longer feature list.
Four groups touch a LIMS in a typical working week, and each needs something different from it. Sampling staff need a client that works without a network and does not ask them to type a sample number twice. Bench analysts need their task list, their template and their instrument results in one place. Reviewers need to see what changed and who changed it. Quality managers need to retrieve a complete record months later, without asking anyone for help.
A system that serves the first two well but leaves the last two searching through folders has not solved the problem; it has moved it. That is why the review trail and the retrieval path are treated as core features rather than reporting add-ons.
Laboratories rarely need every module at once. The practical question is which single gap costs the most today. If sampling records are re-typed at reception, the mobile client pays for itself first. If results are transcribed from instrument workstations by hand, the acquisition module comes first. If reports are assembled in spreadsheets and reviewed on paper, the reporting module removes the bottleneck. If assessment findings are hard to close out, the quality module is the starting point.
Starting with one module also shortens the pilot. A single section can run a limited trial in two to three weeks, and the lessons learned then shape the remaining rollout far more usefully than a long design phase. Institutions that try to launch everything simultaneously usually discover mid-project that one scope assumption was wrong, and by then the change is expensive.
The modules share one data model, so adding a second or third later does not require migration work. That is deliberate: it lets a laboratory grow into the system at its own pace instead of committing to a large programme up front.