No OKRs found for Innovations in Annual 2026.
Build a foundation of tech leadership visibility
Key Results (4)
| Key Result | Lead | Metric | Progress |
|---|
| 2 papers accepted at IJCB | — | 0 → 0 / 2 | |
| Innovatrics is included in 2 EU project consortia submissions | — | 0 → 0 / 2 | |
| 6 public technology talks delivered by Innos | — | 0 → 117 / 6 | |
| 1 PhD student funded | — | 0 → 0 / 1 | |
Build Unified Architecture
Key Results (4)
| Key Result | Lead | Metric | Progress |
|---|
| 70% of teams have a tech lead that is part of the Hybrid Architecture governance model | — | 0% → 0% / 70% | |
| Architecture Decision Record process adopted by 50% of teams (adoption = at least 2 ADR) | — | 0% → 0% / 50% | |
| 100% of repositories with active production code have implemented automated security scanning | — | 0% → 0% / 100% | |
| 100% of repositories with production code follow best practices established by guilds | — | 0% → 0% / 100% | |
Form Innovation capability
Key Results (4)
| Key Result | Lead | Metric | Progress |
|---|
| 2 AI engineers join the team | — | 0 → 0 / 2 | |
| Deliver 4 PoCs linked with our current solutions | — | 0 → 0 / 4 | |
| 2 PoCs transitioned to Solutions / Platform / R&D | — | 0 → 0 / 2 | |
| 10 internal lunch talks | — | 0 → 0 / 10 | |
Improve SWE efficiency using AI tooling
Key Results (4)
| Key Result | Lead | Metric | Progress |
|---|
| 90% of SWEs attend AI workshop tailor made for their work | — | 0% → 82% / 90% | |
| 90% of SWEs use AI tooling to write code daily | — | 0% → 0% / 90% | |
| Achieve 15% increase in story throughput for SWEs that use AI tooling compared to the ones who don't | — | 0% → 0% / 15% | |
| Reduce by 50% time that is needed for context gathering and presentation | — | 0% → 0% / 50% | |
Objective 1: Deliver a unified, secure, and reusable biometric platform foundation adopted across teams.
Key Results (6)
| Key Result | Lead | Metric | Progress |
|---|
| O1KR1-[Q4 2026]: Improve client-side codebase reusability by having at least five significant shared modules (e.g., license validation, Protobuf, MRZ parser) actively used across at least two platforms (web, iOS, Android). | Denis Stiglic | 0 → 0 / 10 | |
| O1KR2-[Q4 2026]: Reduce client-side (serialization)-related security findings to zero. | Denis Stiglic | 0 → 0 / 5 | |
| O1KR3-[Q4 2026]: VPP moves away from bespoke RPC C# services toward the standardized Innovatrics microservice stack by replacing at least 2 legacy services with reusable Biometric Services components. | Peter Pokojny | 0 → 0 / 2 | |
| O1KR4-[Q4 2026]: Increase face matching performance from 13 identifications/core/sec to 200 identifications/core/sec on 1M watchlist in VPP | Peter Pokojny | 13 → 0 / 200 | |
| O1KR5-[Q4 2026]: Validate service reusability by integrating at least one stateless service created during DIS modularization intiative into Biometric record. | Jan Stary | 0% → 0% / 100% | |
| O1KR6-[Q4 2026]: Validate that stateless services are universal and useful by adoption across at least two internal teams. | Jan Stary | 0% → 0% / 100% | |
Objective 2: Launch Innovatrics production SaaS platform that enables IDV to go to market with confidence
Key Results (4)
| Key Result | Lead | Metric | Progress |
|---|
| O2KR1: Platform achieves 99% availability in first 90 days | — | 0% → 0% / 100% | |
| O2KR2-[Q4 2026]: : IDV team independently deploys and operates with < 2 platform-caused BAU incidents (excluding planned maintenance and security remediation incidents). | — | 0 → 0 / 100 | |
| O2KR3-[Q4 2026]: Operationalize a Security & Compliance Baseline with automated daily vulnerability scanning, dependency management, tenant isolation penetration test passed and a target to patch critical items in less than 2 business days | — | 0 → 0 / 100 | |
| O2KR4-[Q2 2026]: Cost visibility operational with daily budget alerts at 90% threshold | — | 0 → 0 / 100 | |
Establish a unified, transparent, and scalable R&D foundation
Key Results (8)
| Key Result | Lead | Metric | Progress |
|---|
| 1 major modality is of production-ready quality within the Biometric Toolkit, supported on all target platforms and languages | — | 0 → 0 / 1 | |
| At the end of year, 50% of deployed models in 2026 have adopted automatic fixture validation and conversion tests in automatic CI/CD pipelines | — | 0% → 0% / 50% | |
| At the end of year, PAD models are retrained every 6 weeks using real-world collected data | — | 0 → 0 / 100 | |
| Face modality PAD is certified as iBeta Level 3 | — | 0 → 0 / 100 | |
| We have coverage for at least 90% of scripts required for IDV opportunities in the sales pipeline | — | 0% → 0% / 90% | |
| 100% of released models have descriptive model cards | — | 0% → 0% / 100% | |
| Software engineering R&D teams comply with ISO 9K/27K | — | 0 → 0 / 100 | |
| 100% of important R&D functionality is covered by whitepapers. (TODO - important functionality will be the result of solution capability catalog -> R&D requirements mapping process) | — | 0% → 0% / 100% | |
Solidify benchmark position
Key Results (6)
| Key Result | Lead | Metric | Progress |
|---|
| Ranked Top 5 in Face Recognition - 1:1 | — | 5.33 → 0 / 5 | |
| Ranked Top 5 in Face Recognition - 1:N | — | 5.7 → 0 / 5 | |
| Ranked Top 3 in Age Estimation | — | 4.5 → 0 / 3 | |
| Ranked Top 1 in Age Estimation demographic bias | — | 10 → 0 / 1 | |
| Civil Fingerprint Recognition achieves the same accuracy as best algorithms of December 2025 | — | 0% → 0% / 100% | |
| Latent Fingerprint Recognition achieves the same accuracy as best algorithms of December 2025 | — | 0% → 0% / 100% | |
Strengthen Organizational Efficiency and R&D Delivery Capacity
Key Results (4)
| Key Result | Lead | Metric | Progress |
|---|
| Improve cross-team model delivery throughput by 50% vs 2025 baseline | — | 0% → 0% / 50% | |
| Maintain average GPU utilization above 70% throughout the year | — | 0% → 0% / 70% | |
| Reach 70% reproducibility traceability coverage for released models | — | 0% → 0% / 70% | |
| Achieve 80% employee engagement and onboarding satisfaction rate within R&D | — | 0% → 0% / 80% | |
Objective 1: Establish an engineering excellence baseline across all engineering teams by standardizing practices and driving architectural health.
Key Results (4)
| Key Result | Lead | Metric | Progress |
|---|
| O1KR1-[Q4 2026]: All solution engineering teams formally adopt and apply the Unified Engineering Standards (e.g., API design, coding, documentation, and terminology). | — | 0% → 50% / 100% | |
| O1KR2-[Q4 2026]: Establish a team member onboarding baseline per team and improve it by 50% | — | 0% → 0% / 50% | |
| O1KR3-[Q4 2026]: Achieve a 25% adoption rate of AI-assisted engineering tools to automate boilerplate, unit testing, and documentation | — | 0% → 80% / 25% | |
| O1KR4-[Q4 2026]: Implement a recognized industry framework (i.e. DORA framework) across all teams to establish delivery baselines and a continuous improvement cycle. | — | 0% → 40% / 100% | |
Objective 2: Deliver a secure, scalable, and compliant SaaS foundation for Enterprise Identity Verification solutions.
Key Results (4)
| Key Result | Lead | Metric | Progress |
|---|
| O2KR1-[Q4 2026]: Define and establish a self-service infrastructure provisioning process with an initial lead-time target of 24 hours for 75% of the cases, measured on a monthly basis for supported service-catalog. | — | 0 → 100 / 100 | |
| O2KR2-[Q4 2026]: Implement a Service Health Program based on Site Reliability Engineering (SRE) principles with an initial set of Service Level Objectives (SLOs) and a compliance rate of 90% on a monthly basis. | — | 0 → 0 / 100 | |
| O2KR3-[Q4 2026]: Operationalize a Security & Compliance Baseline with automated daily vulnerability scanning, dependency management and a target to patch critical items in less than 48 hours. | — | 0 → 0 / 100 | |
| O2KR4-[Q4 2026]: Formalize a customer facing Service Level Agreement (SLA) framework with a customer accessible status dashboard. | — | 0 → 0 / 100 | |
Objective 3: Align engineering execution with business value to maximize return on investment.
Key Results (3)
| Key Result | Lead | Metric | Progress |
|---|
| O3KR1-[Q4 2026]: Establish a Business Capability Model to guide technical investment. | — | 0 → 0 / 100 | |
| O3KR2-[Q4 2026]: Implement a Project vs. Roadmap Capacity Governance model. | — | 0 → 100 / 100 | |
| O3KR3-[Q4 2026]: Standardize the epic scoping and readiness process. | — | 0 → 100 / 100 | |
Objective 4: Facilitate fast flow of value
Key Results (6)
| Key Result | Lead | Metric | Progress |
|---|
| Achieve 80th Percentile Development Time ≤ 7 working days for stories, bugs & tasks (without complicated subsystem teams). | — | 10 → 100 / 7 | |
| Achieve 80th Percentile Cycle Time ≤ 10 working days for stories, bugs & tasks (without complicated subsystem teams). | — | 14.2 → 0 / 10 | |
| Achieve 80th Percentile Development Time ≤ 30 working days for epics. | — | 40 → 0 / 30 | |
| Achieve 80th Percentile Cycle Time ≤ 45 working days for epics. | — | 50 → 0 / 45 | |
| Achieve 80th percentile <2 months R&D-to-Production Cycle Time for new features | — | 4 → 0 / 2 | |
| Achieve 80th percentile <1 month R&D-to-Production Cycle Time for new models without breaking change | — | 3 → 0 / 2 | |