ABOUT US > QUALITY
Quality You Can Trust, From Start to Finish
In high-stakes environments, language quality isn’t subjective. It has to be consistent, defensible, and easy to verify. BIG Language Solutions builds quality into every layer of delivery, across translation and interpretation, so you can communicate with confidence at scale.
ACCREDITATIONS & ASSOCIATIONS
Certifications and Recognition
Quality isn’t just an internal standard for us; it’s validated through independent frameworks and industry recognition.
TRANSLATION
Translation Quality Built for Accuracy and Auditability
We follow an ISO-aligned approach designed to deliver consistent results across teams, content types, and languages.
Qualified linguists with subject-matter expertise and the right level of review based on content risk and regulatory requirements
Structured revision and aligned approvals to maintain a consistent voice and clear meaning
Automated QA checkpoints to catch issues early (terminology, numbers, formatting, completeness)
Final quality verification to confirm the output matches project requirements before delivery
Performance tracking using scorecards and recurring error patterns to drive continuous improvement
Custom MT Engines With Training Quality Controls
When machine translation is used, we don’t treat it as a black box. BIG applies domain-trained engines designed for the terminology and patterns that matter in regulated industries. We can also customize these engines for clients so they understand brand-specific phrasing and terminology.
Our engine quality model includes:
- Curated training data aligned to your domain, content type, and approved terminology
- Controlled updates and versioning so changes are traceable and reversible
- Benchmark testing before release using defined test sets to validate quality gains
- Ongoing monitoring to detect drift as content, terminology, or regulations evolve
This is how we keep MT output consistent so reviewers see fewer surprises and teams spend less time reworking avoidable issues.
AI-Enabled Quality Checks That Strengthen MT and Human Output
AI helps us catch risk earlier, review smarter, and stay consistent across high volumes, without replacing human accountability.
Our automated checks and risk signals help flag:
- Terminology mismatches against approved glossaries
- Numerical errors, date formatting issues, and unit inconsistencies
- Missing segments, truncation, or untranslated text
- Formatting integrity concerns (tags, tables, layout)
- Patterns that indicate quality risk or the need for additional review
If MT is used, these checks work alongside post-editing and human QA gates so the final deliverable is accurate, compliant, and ready for use.
Designed for High-Stakes Communication
When the message matters, every detail makes a difference. BIG supports translation and interpretation with a quality model built for high-risk, high-volume environments, so your communication stays accurate, respectful, and reliable.
INTERPRETATION
Interpretation Quality You Can Rely On, In Real Time
When communication is live, there’s no “fix it later.” That’s why we run interpretation as a controlled, measurable program built for clarity, consistency, and confidence across every interaction.
Qualified, vetted interpreters matched by language pair, modality (OPI/VRI/on-site), and subject-matter needs
Interpreter preparation and terminology alignment so key terms, names, and context stay consistent across encounters
Session QA and monitoring using structured evaluation criteria to review accuracy, protocol adherence, and professionalism
Calibration and coaching loops to apply feedback consistently and strengthen performance over time
Program-level reporting and trend analysis to drive continuous improvement
Interpretation QA at Scale, With Smarter Oversight
Interpretation quality is too important to rely on small, random samples alone. BIG uses an AI-supported interpreter QA workflow built for real-time, high-volume environments, backed by an enterprise-grade interaction recording and analytics platform inside the contact center.
This expands coverage and helps focus review where it matters most.
- Smarter sampling based on signals like sentiment, escalations, complaint history, call length, and call type
- Automated interaction tagging (language, interpreter ID, job type) for faster filtering and investigation
- Speech-to-text transcription to create a searchable record for efficient validation and review
- Behavioral detection that highlights the moments reviewers should focus on (tone shifts, protocol deviations)
Quality Reinforced Through Hiring and Training
Interpretation quality starts long before the first call. We protect consistency by being selective about who we bring into the interpreter pool and by reinforcing expectations from day one, so quality is built into delivery, not retrofitted after the fact.
- Selective recruiting and screening to confirm language proficiency, interpreting skill, and professional readiness before assignment
- Role-based resourcing that matches interpreters to the right modality and use case, so high-stakes interactions get the right level of experience
- Structured onboarding that sets clear expectations for protocols, confidentiality, and client-specific requirements
- Targeted coaching and development focused on the behaviors that matter most in live interactions: clarity, professionalism, and procedure adherence
- Ongoing alignment to keep interpreter performance consistent as needs evolve and volumes scale
BUILT-IN OVERSIGHT
Measure Quality Clearly, Protect Data Confidently
Track usage, reporting, and quality insights through integration, with configurable privacy controls and retention settings.
Full Visibility Through Platform Integration
Quality data shouldn’t live in a silo. Through our integrated platform ecosystem, usage, reporting, and quality insights stay connected to the work that produced them, creating shared visibility into how quality is measured and maintained.
Privacy Controls and Flexible Retention Policies
We support secure, compliance-minded QA. Recordings and transcripts can be retained for a defined review window and configured to align with client policy, including options where calls are not recorded at all. Your requirements drive the configuration.
FAQs
We define quality in translation and interpretation services as accuracy, consistency, and fitness for purpose, meaning the output is correct, aligned to requirements (terminology, formatting, compliance), and ready to use without guesswork.
Yes. Our workflows are ISO-aligned and designed to produce consistent results across teams, languages, and content types.
Quality is reinforced through qualified linguists, subject matter experts, structured revision, automated QA checks (terminology, numbers, formatting, completeness), and a final verification step before delivery.
Humans are always involved in quality. We use automation and AI to surface risk early and make reviewing more efficient, but people remain accountable for accuracy and fitness for purpose. For translation, human review levels are applied based on content risk and requirements. For interpretation, human reviewers use scorecards and targeted coaching supported by AI-enabled sampling and analytics. If a client requests an MT-only workflow for specific use cases, quality is still governed by humans to keep output consistent and predictable.
MT output is managed through controlled workflows, including domain-trained engines, post-editing by qualified linguists, automated QA, and final quality gates.
We use domain-trained engines designed for the terminology and patterns that matter in regulated environments, with governance to keep output consistent over time. When needed, we can also build client-specific engines using your approved terminology and reference content.
We use controlled versioning, benchmark testing prior to release, and ongoing monitoring to detect drift as content, terminology, or requirements evolve.
AI helps us catch issues earlier and review smarter by flagging common risk patterns. Human reviewers remain accountable for final decisions and approvals.
Common flags include terminology mismatches, number/date/unit errors, missing or truncated text, untranslated segments, and formatting/tag integrity problems.
We use an AI-powered QA workflow supported by enterprise contact center interaction recording and analytics, which helps prioritize higher-risk calls and apply consistent scoring.
Scorecards are customizable, but often include protocols (open/close), professionalism, clarity, empathy/tone, background noise control, and compliance with established procedures.
Reviews generate behavior-based feedback and coaching that interpreters and supervisors can track over time, with clear documentation of actions taken.
Yes. Through InterpVault™ platform, clients can access service activity and reporting, and quality insights can be traced back to interpreter jobs and program performance.
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