Artem Gonchakov: Embedding Trust into Every Line of a Claim

Insurance claims often resemble intricate puzzles with pieces scattered across countless sources. Each claim carries its own story, shaped by policy terms, jurisdictional rules, and the unique circumstances of the event. Documents arrive in different formats, details are sometimes missing, and decisions require both careful judgment and adherence to regulations. When handled manually, this complexity slows resolution, creates errors, and leaves customers waiting in uncertainty, testing their patience and trust.

Artem Gonchakovas the CEO of Simplifai, turns this disorder of claims into a well-orchestrated flow. SimplifaiAI Agents act like skilled conductors, ensuring every document, decision, and interaction arrives in the right place at the right time. By removing friction and surfacing clarity, Simplifai empowers insurers to resolve claims faster, cut costs, and keep customers informed with confidence.

Claims as the Core of AI Strategy
Artem explains that he steers Simplifai with a simple rule: focus on one problem at a time until the company is the best at it. In the insurance sector, that problem is claims. Claims operations combine process nuance, legacy technology, unstructured data, regulatory constraints, human judgment, and wide variance across claim types and jurisdictions. It is the point where insurers keep their promises to customers and where complexity drives cost, cycle time, and customer frustration when processes lag. Artem emphasizes that this is why Simplifai chose to specialize in claims.

The company’s strategy is to become the world leader in applying Agentic AI to claims. This involves addressing the entire lifecycle of a claim, from intake to processing, payout, and closure, initially focusing on Motor, Property, Travel, and Bodily Injury claims. Simplifai does not attempt to be everything to everyone but builds a composable platform that assembles AI Agents from reusable skills and orchestrates them within the insurer’s existing systems and policies. Artem highlights that claims demand depth over breadth, rewarding mastery rather than superficial solutions.

Redefining Insurance Operations
Artem defines Agentic AI as the next stage of AI evolution, moving from primitive rule-based automation, isolated models, digital assistance or point solutions tointelligent systems that orchestrate work. An AI Agent is a governed workflow composed of modular skills that perceive, decide, act, and learn within explicit guardrails.Simplifai offers insurers a supervised control mode, where every action is predefined, and human oversight is applied at key steps. This approach aligns with the strong preference within the insurance sector, where managing risk and ensuring accountability are critical. While autonomous handling of low-risk decisions is technically possible, most insurers prioritize the supervised model to maintain full control and confidence.

He contrasts this with traditional insurance AI, which is usually fragmented, such as individual fraud models, OCR tools, or RPA Bots. Agentic AI, by contrast, can advance an entire claim end-to-end. The agent collects missing documents, updates core systems, communicates with customers, coordinates vendors, and escalates when needed. Artem stresses that an AI Agent is not simply a digital employee; it is a complex, transparent system that composes multiple capabilities, reasons with context, and operates as a reliable teammate. The distinctiveness of the Simplifai Platform lies in its composability, observability, and human compatibility. Agents are built from a Skills Library, orchestrated visually in Flow Builder, and monitored through Know Your Agent dashboards. Together, these elements create synergy across the platform, enabling insurers to accelerate innovation cycles while maintaining transparency and control.

maintaining service speed. Artem ensures that value is embedded in every engagement by establishing baseline metrics, defining a value hypothesis for each workflow, and continuously monitoring performance through the Know Your Agent dashboards. Adjustments are made to improve skills, templates, or handoffs whenever necessary, creating a cadence of measurement, learning, tuning, and expansion.

Trust as the Hidden Driver of Innovation

Artem explains that Simplifai delivers purpose-built AI Agents designed to handle a wide range of tasks across the claims process while continuously expanding their capabilities. One notable example is vehicle damage outlay assessments for a UK insurer. Claims handlers often spent excessive time reviewing engineer reports and invoices to determine if costs aligned with internal benchmarks. The AI Agent now reviews incoming documentation, flags duplicate charges or missing documents, compares costs against internal limits, and provides structured recommendations, freeing up handler time for more strategic tasks while improving cost control and fraud detection.

Another example involves document intake for property claims for a US-based insurer. High volumes of emails and attachments from contractors made it difficult to accurately link documents to the correct claim. The AI Agent identifies the appropriate claim, categorizes content using over seventy-five labels, converts files into usable formats, splits emails with multiple document types, detects embedded URLs, categorizes inline images, and merges photos into single PDFs. This process enhances data quality, speeds up processing, and provides claim handlers with prioritized access to critical documents. The AI Agent continues to evolve, now working toward generating complete claim summaries, identifying inconsistencies, and recommending next actions within the same workflow.

Building Secure and Compliant AI from Day One
Artem emphasizes that Simplifai builds enterprise trust from day one. The company implements ISO-style controls, SOC 2 certification, GDPR-aligned practices, and strict data residency options. Privacy by design is central, including least-privilege access, encryption in transit and at rest, environment isolation, granular audit logs, versioning of skills and models, and automated data lifecycle management. Regular security reviews, penetration testing, and third-party audits ensure the highest standards are maintained.

AI is also leveraged for compliance, including bias checks during model training, guardrails on generative outputs, and programmatic controls to prevent actions without mandatory approvals or required data. Artem stresses that by prioritizing trust and compliance, Simplifai actually accelerates project timelines. Regulatory questions are addressed before claims are processed, reducing rework, speeding approvals, and enabling clients to realize value more quickly.

Overcoming Barriers to AI Transformation
Artem identifies four recurring challenges in scaling AI solutions within the traditionally conservative insurance sector. First, legacy technology stacks, characterized by heterogeneous cores, brittle interfaces, and siloed data, often slow transformation. Simplifai addresses this through a non-invasive integration layer using connectors, event listeners, and APIs, allowing AI Agents to orchestrate work without requiring a complete system overhaul.

Second, data quality issues such as unstructured inputs, inconsistent templates, and missing information create processing delays. The company mitigates these challenges through robust extraction skills, targeted data-gathering steps, and completeness checks that request precise next items rather than vague inputs. Third, market noise and inflated promises from other AI providers can overwhelm buyers. Artem notes that Simplifai differentiates itself through live demos on customer data, rapid pilot projects, and transparent dashboards that provide clear insight into automation, accuracy, handoffs, and value. Finally, AI maturity and urgency vary across organizations. Simplifai addresses this through education, expectation management, and by using baseline metrics such as backlog age, leakage, overtime, and complaint rates to demonstrate the need for change.

The strategies that have proven effective are consistent: co-design with cross-functional teams, radical transparency including limitations, customer-centric prioritization, and outcome-aligned commercial models. Simplifai starts with one real problem, demonstrates value quickly, and only scales when measurable benefits are visible in operations, building confidence and consensus in cautious environments.

Metrics that Make AI Agents Accountable
Artem explains that Simplifai measures the performance of AI Agents by focusing on work completed, quality achieved, and value created. Key metrics include reduction in cost per claim, efficiency gains such as hours saved and AI coverage by task, speed improvements in claim cycle times and time to first response, accuracy in data extraction, decision confidence, and leakage control, as well as scalability in claims handled per full-time equivalent and elasticity during peak periods.

As CEO, Artem emphasizes a clear cause-and-effect chain: reliable agent performance reduces handoffs and errors, accelerates settlements, enhances clarity in communication, boosts customer satisfaction and retention, and ultimately lowers cost per claim. The Know Your Agent dashboards provide weekly insight into these metrics. Any weak link in the chain prompts targeted adjustments to workflows, skills, or policy thresholds, ensuring that value remains measurable and compounding.

Envisioning the Future of AI in Insurance
Artem foresees the next decade as an era of amplified human teams, where AI Agents will handle 80 to 90 percent of routine work in many claim segments. Human professionals will increasingly focus on managing AI Agents and engaging in tasks requiring judgment, negotiation, empathy, and creativity.

Three shifts will define this period. First, AI co-pilots for every role will assist adjusters and handlers by summarizing case files, surfacing precedents, suggesting next actions, and drafting communications grounded in policy facts. Leaders will manage hybrid human-AI teams using live value telemetry. Second, multi-modal intelligence will combine text, images, voice, and video to deliver sophisticated, explainable outputs such as photo-based damage assessments integrated with policy rules. Third, governed autonomy will allow AI Agents to make straight-through decisions in low-risk scenarios, while maintaining built-in explainability, auditability, and rollback capabilities for regulators and customers.

Simplifai is preparing for this transformation by investing heavily in research and experimentation. The company continues to expand its Skills Library across the claims lifecycle, enhance Flow Builder for non-technical workflow composition, and evolve KYA dashboards from reporting to actionable recommendations. Additionally, end-to-end AI Agents are being developed to achieve true governed autonomy, ensuring that advanced capabilities move from concept to daily operational reality safely, measurably, and repeatably.

Principles Fueling Innovation and Growth
Artem emphasizes five leadership principles that guide him in managing both technological innovation and business growth at Simplifai. First, radical transparency, sharing numbers, risks, and trade-offs internally and with customers, builds trust and accelerates progress. Second, meaningful work ensures that every sprint ties directly to a real claim pain or customer outcome, motivating teams by showing them who benefits and how. Third, he focuses on tackling hard problems with compounding value, such as claims orchestration, rather than pursuing superficial demos. Fourth, Simplifai operates as a purpose-driven business, dedicated to helping insurers keep their promise to customers faster, fairer, and at scale. Finally, Artem enforces a no-nonsense approach, avoiding hype and addressing flat metrics or underperforming features promptly to maintain credibility.

This culture manifests in small, accountable teams with clear outcomes, engineers owning flows end-to-end, and a cadence that favors shipping with guardrails over endless polishing. Innovation with purpose, habitual measurement, and a bias for weekly improvement are central to Simplifai’s growth.

Co-Creating the Future
Artem highlights the importance of partnerships and collaborations with insurance companies in driving Simplifai’s success. The company engages in strategic collaborations where product development and innovation are co-created with clients. Each account has a dedicated Solution Manager working closely with customer teams to define problems, configure flows transparently, and review outcomes through shared dashboards.

Effective collaborations, according to Artem, share four traits. First, aligned incentives with pricing structures that reward adoption and outcomes ensure mutual benefit. Second, a combination of executive sponsorship and frontline ownership guarantees vision at the top and operational reality at the ground level. Third, phased expansion, demonstrating one high-value workflow before scaling in waves across intake, triage, handling, and payment, builds trust and value incrementally. Fourth, joint storytelling through case studies, events, or analyst briefings amplifies learning across the industry. Success is measured when customers name their AI Agent, review its performance monthly, and request subsequent waves of transformation.

Guiding AI Adoption in Traditional Industries
Drawing from his experience, Artem advises executives and startups introducing AI solutions in conservative industries like insurance to begin with a small, real problem and validate it quickly. Issues such as backlog at intake, missing documents, or slow first responses are ideal starting points. The solution must achieve measurable impact within weeks to prove value.

He stresses the importance of achieving product-market fit by ensuring the AI solution aligns with actual work rather than theoretical process diagrams. Moving quickly with built-in safety measures such as human-in-the-loop, thresholds, audit trails, and data protection accelerates adoption and procurement. Close collaboration with customers through co-design involving claims, IT, and compliance teams, supported by dashboards that transparently report results, builds trust and accountability.

Artem also encourages teams to remain lean and humble, iterating quickly and fixing issues openly to allow credibility to compound. Above all, he emphasizes the mission: AI must help insurers fulfill their promise to customers faster, fairer, and at scale, without compromising the human touch. This principle serves as the guiding lens for Simplifai’s work and for any team bringing AI into traditional industries.