ZTABS provides quality assurance and software testing for Denver's high-stakes industries — fintech platforms serving Colorado's growing digital banking sector with NCUA and CFPB compliance testing, cannabis point-of-sale systems where: Metrc integration bugs create MED compliance violations for 2,800+ licensed operators, aerospace flight software tested to DO-178C standards for Denver's Lockheed Martin and Ball Aerospace corridor, and outdoor recreation apps tested at 14,000+ feet in sub-zero temperatures with zero cellular connectivity.
Denver's software testing challenges are shaped by: regulated industries where bugs have compliance consequences, extreme environmental conditions where software must perform reliably, and: a technical ecosystem where: system integration across government and industry platforms creates: complex testing requirements. QA in Denver differs from general software testing because: compliance failures are not just bugs — they are violations (in cannabis: a Metrc integration bug that fails to: record a transfer creates a: regulatory violation that can result in: license suspension, fines, or: closure — in fintech: a transaction processing error can violate: federal banking regulations — in aerospace: a software defect in flight systems can result in: mission failure with: catastrophic consequences — Denver's QA must: verify not just: functional correctness but: regulatory compliance at every integration point), environmental conditions stress software in ways that: standard testing does not cover (mobile applications must function at: 14,000+ feet where: GPS accuracy degrades, batteries drain faster in cold, cellular coverage disappears, and: screen readability suffers in: intense high-altitude sunlight — these conditions cannot be: simulated in: a lab — Denver QA teams test in: the actual mountain environments where: software will be used), integration complexity spans: government systems, industry platforms, and: specialized hardware (cannabis software must: integrate with: Metrc (state tracking system), MED licensing databases, laboratory information management systems (LIMS), and: payment processors — each with: specific API behaviors, rate limits, and: error handling requirements — aerospace software integrates with: satellite systems, ground stations, and: mission control — fintech integrates with: banking core systems, payment networks, and: regulatory reporting systems), and Colorado SB 24-205 creates new testing requirements for AI systems (effective February 2026: high-risk AI systems must be: tested for bias, explainability, and: safety — creating: an entirely new category of: QA testing that: Denver companies must: implement for: AI-powered products in: regulated industries).
Denver's QA testing demand spans fintech, cannabis technology, aerospace, outdoor tech, and healthcare. Fintech QA: digital banking testing (Colorado's credit unions (40+ chartered) and: community banks are: building digital banking platforms to: compete with: national fintechs — QA testing for: account management, transaction processing, ACH/wire transfers, mobile check deposit, and: bill pay — with: NCUA (National Credit Union Administration) and: CFPB (Consumer Financial Protection Bureau) compliance verification — testing: edge cases that: expose: compliance risk: partial transactions, duplicate submissions, timezone boundary transactions, and: concurrent access), payment processing testing (testing: payment platforms for: accuracy, security, and: regulatory compliance — PCI DSS compliance verification, fraud detection system testing, and: transaction reconciliation — including: Colorado-specific requirements like: the Colorado Privacy Act (CPA) for: consumer data handling), and cryptocurrency and digital asset testing (Colorado has: embraced cryptocurrency — accepting: crypto for: state tax payments since 2022 — fintech platforms handling: digital assets require: testing for: wallet integration, exchange connectivity, blockchain confirmation handling, and: regulatory reporting for: FinCEN requirements). Cannabis Technology QA: Metrc integration testing (the most critical testing domain for: cannabis technology — every cannabis software system must: correctly report: seed-to-sale tracking data to: Metrc — testing: covers: plant tag creation and: transfer, harvest batch reporting, manufacturing lot tracking, package creation and: labeling, transfer manifest generation and: acknowledgment, waste disposal reporting, and: sales recording — each: Metrc API endpoint has: specific validation rules, error codes, and: rate limits — comprehensive testing ensures: that: every operational action generates: correct Metrc data — failure means: compliance violations), POS system testing (cannabis point-of-sale systems have: unique testing requirements: age verification (testing: that the system correctly verifies: customer age at: every transaction and: rejects: underage customers), Metrc real-time sync (every sale must: be recorded in: Metrc — testing: that the POS correctly debits: inventory and: reports: the transaction — including: error handling when: Metrc is: unavailable), product display compliance (MED rules restrict: how products are: displayed — testing: that the POS does not: show: medical products to: recreational customers or: display: non-compliant product information), payment handling (cannabis payment is: complex — cash, debit, and: limited electronic options — testing: that the POS correctly handles: each payment method including: cash calculation, tip handling, and: receipt generation)), and multi-location testing (operators with: multiple dispensaries need: software that: works consistently across: locations — testing: inventory transfers between: locations (with: Metrc manifests), consolidated reporting, location-specific pricing and: promotions, and: multi-location user permissions). Aerospace QA: DO-178C compliance testing (aerospace software for: Denver's Lockheed Martin, Ball Aerospace, and: ULA must: meet: DO-178C (Software Considerations in Airborne Systems and Equipment Certification) standards — the most rigorous software testing standard in: commercial use — requiring: requirements-based testing, structural coverage analysis (MC/DC — Modified Condition/Decision Coverage), traceability from: requirements through: design to: test cases, and: configuration management of: all test artifacts), satellite software testing (testing: satellite flight software, ground station software, and: mission planning systems — with: challenges specific to: space operations: the software cannot be: patched after launch (testing must: catch: every defect before: deployment), real-time constraints (satellite operations have: hard deadlines for: command execution), radiation effects (testing: for: single-event upsets and: degraded memory), and: communication delays (testing: autonomous operation during: ground contact gaps)), and simulation and hardware-in-the-loop (testing: aerospace software with: hardware simulators that: replicate: satellite subsystems, orbital mechanics, and: communication links — verifying: that software correctly controls: hardware in: realistic simulated environments before: deployment to: actual spacecraft). Outdoor Recreation App QA: altitude and environmental testing (testing: mobile apps at: actual Colorado altitudes and: conditions — GPS accuracy testing (comparing: reported position vs. known position at: various altitudes and: terrain types — GPS accuracy degrades: in steep terrain and: at high altitude due to: satellite geometry), battery drain testing (measuring: battery consumption at: various temperatures — from: 80°F summer days to: -20°F winter mountain conditions — cold temperatures significantly reduce: battery capacity), and offline functionality testing (testing: every app feature with: airplane mode enabled — verifying: data caching, offline navigation, queued transaction handling, and: sync behavior when: connectivity returns)), and field testing program (QA testing for: outdoor apps requires: actual field testing — we maintain: a field testing program that: tests apps at: representative Colorado locations: Mount Evans (14,264' — high altitude, exposed), Eisenhower Tunnel (I-70 connectivity transition), Vail Pass (winter conditions, variable connectivity), Rocky Mountain National Park (varied terrain, limited coverage), and: urban Denver (5,280' baseline, full connectivity) — providing: real-world performance data that: lab testing cannot replicate).
Our QA testing approach for Denver combines: regulatory compliance verification, environmental stress testing, and: integration validation specific to Colorado's industries. Phase 1 — Test Strategy (1-2 weeks): designing the testing approach: risk assessment (identifying: the highest-risk areas for: each product — for cannabis POS: Metrc integration is: the highest risk (compliance violations) — for fintech: transaction accuracy is: the highest risk (financial loss and: regulatory violations) — for outdoor apps: offline functionality is: the highest risk (user safety) — the test strategy allocates: effort proportional to: risk), compliance mapping (mapping: every regulatory requirement to: specific test cases — for cannabis: MED rules mapped to: Metrc API behaviors mapped to: test scenarios — for fintech: NCUA regulations mapped to: transaction processing rules mapped to: test scenarios — for aerospace: DO-178C requirements mapped to: structural coverage targets — this compliance mapping ensures: that every regulatory requirement is: tested explicitly), test environment design (designing: test environments that: replicate: production conditions — for cannabis: Metrc sandbox environment configuration, lab LIMS simulator, and: payment processor test mode — for aerospace: hardware-in-the-loop simulators, orbital mechanics models, and: communication link simulators — for outdoor: field testing locations, environmental chambers for: temperature testing, and: RF-shielded rooms for: connectivity testing), and SB 24-205 test planning (for AI-powered products: designing: bias testing methodology, explainability verification, and: safety testing — identifying: the specific SB 24-205 requirements applicable to: the product and: creating: test cases for: each requirement)). Phase 2 — Test Development (2-4 weeks): building the tests: automated test suites (building: automated tests for: repeatable verification — unit tests for: business logic (calculation accuracy, rule enforcement), integration tests for: external system communication (Metrc API, banking core, payment networks), and: end-to-end tests for: complete user workflows — automated tests run: on every code change, catching: regressions before: they reach: production), compliance test cases (detailed test cases for: every mapped regulatory requirement — each: test case: includes: the regulatory requirement reference, the expected behavior, the test steps, the acceptance criteria, and: the evidence to: capture — for Metrc integration: test case 3.315.A: "Verify that harvest batch weight reported to Metrc matches the scale reading within 0.1 gram tolerance" — these test cases form: the compliance evidence that: regulators can: audit), performance testing (load testing, stress testing, and: endurance testing for: systems that: must handle: peak demand — for cannabis POS: testing: Black Friday and: 4/20 (April 20) peak sales volumes — for fintech: testing: month-end processing, tax season volumes, and: market volatility spikes — for outdoor apps: testing: Saturday morning ski season peaks when: tens of thousands of: users simultaneously access: trail and: traffic information), and security testing (penetration testing, vulnerability scanning, and: security code review — for fintech: PCI DSS compliance testing, OWASP Top 10 verification, and: authentication/authorization testing — for cannabis: testing: that user access controls prevent: unauthorized Metrc reporting, that: payment data is: encrypted, and: that customer PII is: protected per: Colorado Privacy Act — for aerospace: testing: against: relevant security standards for: space systems)). Phase 3 — Test Execution (ongoing): running the tests: continuous integration testing (automated tests run: on every code commit — unit tests, integration tests, and: critical path end-to-end tests — providing: immediate feedback to: developers when: changes introduce: defects), sprint testing cycles (each development sprint includes: a testing cycle — new features receive: functional testing, regression testing verifies: that new changes did not: break: existing functionality, and: compliance testing verifies: that regulatory requirements remain: satisfied), environmental and field testing (periodic: field testing for: outdoor and: altitude-sensitive applications — our field testing program runs: monthly during: active development and: quarterly during: maintenance — testing: at representative Colorado locations with: documented conditions (temperature, altitude, connectivity, weather)), and user acceptance testing (coordinating: UAT with: real users — for cannabis: dispensary staff testing: POS workflows in: an actual dispensary environment — for outdoor: beta testers using: the app on: actual hikes and: ski days — for fintech: bank staff testing: transaction workflows with: test accounts — UAT catches: usability issues and: workflow gaps that: automated testing cannot: detect)). Phase 4 — Quality Reporting (continuous): communicating testing results: compliance evidence (generating: compliance documentation from: test results — for cannabis: Metrc integration test reports showing: every API endpoint tested, expected vs. actual behavior, and: pass/fail status — for DO-178C: complete test case execution records with: structural coverage analysis showing: MC/DC coverage meets: the required level — for fintech: PCI DSS and: NCUA compliance test evidence organized by: regulatory requirement), defect management (tracking: defects by: severity, type, and: regulatory impact — high-severity defects (compliance violations, data loss, security vulnerabilities) are: escalated immediately — defect trends are: analyzed to: identify: systemic quality issues that: require: process or: architecture changes rather than: individual bug fixes), and quality dashboards (real-time visibility into: quality metrics — test pass rates, defect density, code coverage, compliance coverage, and: field testing results — enabling: product teams to: make: informed release decisions based on: objective quality data)).
Fintech / Cannabis Technology
A Denver-based cannabis technology company had: built a point-of-sale platform used by: 85 dispensaries across: Colorado, with plans: to expand to: 12 additional states. The platform handled: approximately $2.1M in: daily transactions across: all locations and: integrated with: Metrc for: seed-to-sale compliance tracking. The problem: the company had: grown rapidly without: a structured QA program. Testing was: ad hoc — developers wrote: some unit tests, a QA analyst manually tested: new features, and: bug reports from: dispensaries served as: the primary defect detection mechanism. This approach was: failing as: the platform scaled. Specific issues: (1) Metrc compliance failures: in the prior 6 months, 14 dispensary clients had: received: MED notices for: Metrc discrepancies traceable to: POS software bugs — inventory counts in: the POS did not match: Metrc records due to: edge-case transaction handling (voided sales, partial returns, employee discounts, and: split-tender transactions were: not consistently synced to: Metrc). Two dispensaries had: received: formal warnings — a third violation could: result in: license suspension. (2) Payment accuracy: 3 instances of: transaction amount discrepancies — where: the amount charged to: the customer's debit card did not: match: the receipt total — discovered: by dispensary staff during: end-of-day reconciliation — each: requiring: manual correction and: customer notification. (3) Multi-state expansion risk: expanding to: 12 additional states meant: integrating with: each state's tracking system (BioTrack in some states, Metrc in others, LEAF Data in Washington) — each: with different APIs, validation rules, and: compliance requirements — the current ad hoc testing approach could not: scale to: handle: 13 state-specific compliance test suites. (4) Scale concerns: the platform had: grown from: 20 to: 85 dispensaries in: 18 months — peak daily transaction volume had: increased 4x — load testing had: never been: performed — the development team suspected: but had not: verified: that the system would: handle: continued growth without: performance degradation.
We designed and implemented a comprehensive QA program over 8 weeks — establishing: the testing infrastructure, processes, and: team capabilities that: the company needed. Metrc Integration Test Suite: complete API coverage (we built: an automated test suite that: tested: every Metrc API endpoint the POS used — 34 endpoints covering: plant management, harvest batch processing, package creation, transfer management, sales recording, waste reporting, and: inventory adjustment — each: endpoint tested for: correct data formatting, required field validation, error handling, and: edge cases), edge case library (we identified and: catalogued: 127 transaction edge cases that: could cause: Metrc discrepancies — voided sales (full void vs. partial void vs. void after: Metrc sync), returns (same-day return vs. next-day return vs. return of: partial quantity), split-tender transactions (cash + debit, with: various rounding scenarios), employee transactions (employee discount calculation and: Metrc reporting), loyalty point redemption (how: point-based discounts interact with: Metrc price reporting), and: concurrent transactions (two registers selling: the same product simultaneously — testing: inventory deduction and: Metrc reporting for: race conditions) — each: edge case had: a specific test case with: expected Metrc behavior documented), and state-specific test modules (anticipating: multi-state expansion: we designed: the Metrc test suite as: a modular framework where: the core test logic was: shared but: state-specific validation rules, API differences, and: compliance requirements were: encapsulated in: state modules — building: the Colorado module completely and: creating: module templates for: the 12 expansion states)). Payment Accuracy Testing: transaction testing (comprehensive testing of: every payment path: cash (calculation of: change due for: every combination of: denominations — testing: the edge cases that: had caused: discrepancies: transactions with: tax-inclusive pricing vs. tax-added pricing, tip handling, rounding of: fractional cents, and: discount application sequence (percentage discount before: or after: tax)), debit card (authorization amount vs. settlement amount matching, partial authorization handling, timeout and: retry behavior, and: offline authorization with: floor limits), and split tender (correct allocation of: payment across: methods, receipt display accuracy, and: reconciliation report accuracy)), reconciliation testing (end-of-day reconciliation was: where: previous discrepancies had been: discovered — we built: automated reconciliation testing that: processed: a day's worth of: simulated transactions (500-800 transactions matching: the daily volume of: a busy dispensary) and: verified: that: POS transaction records, payment processor records, and: Metrc sales records all: reconciled to: the same totals within: acceptable tolerance ($0.01)), and daily audit automation (an automated daily check that: compared: POS sales totals, Metrc reported sales, and: payment processor settlement amounts for: each live dispensary — flagging: any discrepancy greater than: $0.01 for: immediate investigation — catching: potential issues in: production before: dispensary staff discovered: them during: manual reconciliation)). Performance Testing: load testing (simulating: peak transaction volumes: 4/20 (the cannabis industry's biggest sales day — typically: 3-5x normal volume), Black Friday, and: general growth scenarios — testing: the system's behavior at: 2x, 5x, and: 10x current peak volume — identifying: the bottlenecks: database query performance at: high concurrent transaction rates, Metrc API rate limiting at: peak reporting volumes, and: payment processor timeout behavior under: load), stress testing (pushing: the system beyond: its designed capacity to: identify: failure modes — does: the system degrade gracefully (slower but: correct) or: fail dangerously (fast but: incorrect or: data-losing)? — we identified: 3 failure modes that: could cause: data integrity issues under: extreme load and: implemented: circuit breakers to: prevent: those failures), and endurance testing (running: the system under: sustained load for: 72 hours — identifying: memory leaks, connection pool exhaustion, and: performance degradation over time — critical for: a system that: runs continuously in: dispensaries that: may not: restart the POS application for: weeks)). SB 24-205 AI Testing: the POS platform included: AI-powered product recommendations (suggesting: products to: budtenders based on: customer purchase history and: product similarity) — qualifying: as a potential high-risk AI system under: SB 24-205. We implemented: recommendation bias testing (verifying: that the AI did not: systematically recommend: higher-priced products, discriminate based on: customer demographics captured in: loyalty data, or: recommend: products based on: characteristics that: would constitute: improper marketing under: MED rules), explainability testing (verifying: that each recommendation could be: explained — "Recommended because: this customer has: purchased: similar strains in: the past" — not: "Recommended by: the algorithm"), and human override testing (verifying: that budtenders could: easily dismiss or: override: AI recommendations and: that: overrides were: logged for: SB 24-205 audit purposes).
The QA program eliminated compliance failures and enabled confident multi-state expansion. Metrc Compliance: zero Metrc discrepancies: in the 6 months following: QA program implementation: zero MED notices related to: POS software defects — down from: 14 in: the prior 6 months — the automated edge case testing caught: 23 potential Metrc discrepancy bugs during: development before: they reached: production — each: of these bugs would: have caused: compliance issues at: one or more: dispensary clients. Edge case coverage: the 127 identified edge cases were: all tested automatically on: every code release — providing: confidence that: changes to: one part of the system did not: introduce: Metrc discrepancies through: unexpected edge case interactions. Payment Accuracy: zero payment discrepancies: after implementing: the comprehensive payment testing suite: zero transaction amount discrepancies in: 6 months — down from: 3 in: the prior 6 months — the automated reconciliation testing caught: 8 potential discrepancy bugs during: development. Daily audit: the automated daily reconciliation check ran: across all: 85 live dispensaries — flagging: 12 minor discrepancies in: 6 months — all: traced to: dispensary-side operational issues (incorrect cash handling, register errors) rather than: software defects — providing: evidence that: the software was: functioning correctly. Performance: 4/20 readiness: the platform handled: 4/20 (April 20) traffic — 4.2x normal daily volume — with: no performance degradation, no transaction failures, and: no Metrc reporting delays — this was: the first year the company survived: 4/20 without: a production incident. Headroom: load testing confirmed: the platform could: handle: 8x current peak volume — providing: comfortable headroom for: continued growth. Multi-State Expansion: accelerated timeline: the modular test framework reduced: the estimated QA effort for: each new state from: 6 weeks (custom test development) to: 2 weeks (state module configuration and: validation) — accelerating: the multi-state expansion timeline by: approximately 4 months. First expansion: the QA program enabled: confident launch in: Illinois and: Michigan as: the first expansion states — both: launched with: zero compliance defects in: the first 90 days. Financial Impact: MED violation prevention: each avoided MED notice was: estimated to: cost: $5,000-$25,000 in: attorney fees, remediation costs, and: client management — the 23 caught defects represented: estimated avoidance of: $115,000-$575,000 in: violation costs. Client retention: dispensary client churn dropped from: 8% (prior year — driven by: compliance concerns) to: 2% (post-QA program) — retaining: approximately 5 additional clients worth: $360,000 in: annual recurring revenue. Development cost: $164,000 (8 weeks of: QA program design and: implementation). Annual QA operating cost: $96,000 (dedicated QA engineer + testing infrastructure). First-year ROI: estimated 200-400% (based on: violation avoidance, client retention, and: expansion acceleration value vs. QA investment).
Automated unit, integration, and E2E tests with Jest, Cypress, Playwright, and more.
Exploratory testing, regression, and UAT to validate real-world usage and edge cases.
Load, stress, and scalability tests to ensure apps perform under real traffic.
Tests integrated into your pipeline for continuous feedback on every change.
Test plans, coverage analysis, and risk-based prioritization for efficient QA.
Denver's QA testing landscape includes national QA firms, freelance testers, and internal QA teams. (1) National QA firms (Accenture, Cognizant, TCS) — large-scale testing capability but: no cannabis regulatory knowledge, no altitude/environmental field testing program, and: high overhead costs. (2) QA staffing agencies — can provide testers but: not cannabis Metrc expertise, DO-178C certification experience, or: SB 24-205 AI testing methodology. (3) Freelance QA — cost-effective for: basic functional testing but: cannot design: comprehensive compliance test programs for: regulated industries. ZTABS provides QA testing for Denver's regulated industries with: Metrc integration testing expertise, altitude and environmental field testing, DO-178C aerospace testing capability, and SB 24-205 AI testing methodology.
QA testing in Denver ranges by regulatory complexity and testing scope. QA Assessment and Strategy (test strategy design, risk mapping, 1-2 weeks): $15,000-$30,000. Test Suite Development (automated tests, compliance mapping, 4-8 weeks): $60,000-$140,000. Comprehensive QA Program (full program design and implementation, 8-12 weeks): $120,000-$250,000. Ongoing QA operations: $8,000-$20,000/month for: continuous testing, field testing, compliance monitoring, and: test maintenance. ZTABS delivers at $150-250/hr — QA engineers with Denver regulatory and environmental testing expertise.
Verified reviews from real client engagements — sourced from our public testimonial archive and Clutch profile.
My experience is throughout positive. Communication, service, the short response times and the flawless execution of a challenging topic was absolutely great. ZTABS is definitely my first choice again.
Christian Neff
Bank Software Advisory · Bank Software Advisory
Fintech
Fantastic Agency! I couldn't fault them even if I tried. They always go above and beyond to meet your expectations and always produces quality work. Thank you ZTABS.
Stephanie Kal
CEO · Beauty Finder Australia
Marketplace
It has been great working with ZTABS. They bounce off the ideas along the way. Amazing Experience.
Joel Rowe
CEO · Drill Quoter
Marketplace
We don't just contract. We ship and operate our own software. 23 products in production.
Common questions about qa & testing for Denver businesses
We build automated test suites covering every Metrc API endpoint the software uses — typically 30-40 endpoints for a full POS system. Each endpoint is tested for correct data formatting, required field validation, error handling (what happens when Metrc is unavailable?), and edge cases (voided sales, partial returns, split-tender transactions, concurrent register operations). We maintain a library of 125+ cannabis transaction edge cases that we have identified through real-world dispensary operations. Every code release runs through the complete Metrc test suite before deployment. The goal: zero Metrc discrepancies reaching production.
ZTABS is a remote-first qa & testing agency serving Houston businesses — including test automation, manual qa, performance testing. We work with Energy & Oil/Gas, Healthcare & Biotech, Aerospace & Defense companies in Houston, TX via timezone-aligned engineers and async workflows; we do not have a local office, and we are explicit about that with every client.
QA & Testing in New York, NYZTABS is a remote-first qa & testing agency serving New York businesses — including test automation, manual qa, performance testing. We work with Finance & Fintech, Media & Advertising, Fashion & Retail companies in New York, NY via timezone-aligned engineers and async workflows; we do not have a local office, and we are explicit about that with every client.
QA & Testing in Los Angeles, CAZTABS is a remote-first qa & testing agency serving Los Angeles businesses — including test automation, manual qa, performance testing. We work with Entertainment & Media, E-commerce & DTC Brands, Gaming & AR/VR companies in Los Angeles, CA via timezone-aligned engineers and async workflows; we do not have a local office, and we are explicit about that with every client.
Web Development in Denver, COZTABS is a remote-first web development agency serving Denver businesses — including full-stack development, progressive web apps, api development. We work with Outdoor & Lifestyle Tech, Aerospace & Defense, Cannabis Tech companies in Denver, CO via timezone-aligned engineers and async workflows; we do not have a local office, and we are explicit about that with every client.
Web Design in Denver, COZTABS is a remote-first web design agency serving Denver businesses — including ui/ux design, responsive design, custom interfaces. We work with Outdoor & Lifestyle Tech, Aerospace & Defense, Cannabis Tech companies in Denver, CO via timezone-aligned engineers and async workflows; we do not have a local office, and we are explicit about that with every client.
AI Development in Denver, COZTABS is a remote-first AI development agency serving Denver businesses — including llm integration & fine-tuning, ai agents & automation, rag & knowledge systems. We work with Outdoor & Lifestyle Tech, Aerospace & Defense, Cannabis Tech companies in Denver, CO via timezone-aligned engineers and async workflows; we do not have a local office, and we are explicit about that with every client.
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