Eight practice areas. Over 80 service lines. One mission-focused SDVOSB with practitioner-grade expertise across cybersecurity, GRC, and artificial intelligence.
Foundation-level security and compliance services backed by 25+ years of hands-on federal and commercial experience. From policy to audit — we do the work, not just the advice.
End-to-end GRC program development including policy creation, risk management framework implementation, control design, and continuous monitoring. We translate complex regulatory requirements into actionable, sustainable governance structures that stand up to scrutiny.
Advisory services aligned to NIST 800-53, the NIST Cybersecurity Framework, and FedRAMP requirements — including SSP development, control documentation, gap assessments, readiness reviews, and ongoing authorization support.
Full PCI-DSS support including scoping, gap analysis, remediation planning, evidence collection, and QSA liaison coordination. Direct enterprise-scale experience managing PCI-DSS across 16,000+ retail locations.
Federal SA&A support under both legacy DIACAP and current RMF frameworks — C&A package development, control assessments, ATO package preparation, and POA&M management.
TPRM programs that systematically assess vendor security posture, identify supply chain risk, and establish ongoing monitoring. Risk-tiered vendor inventories, assessment questionnaires, and escalation workflows tailored to your risk appetite.
Programs that build genuine security culture through role-based content, metrics-driven measurement, and continuous reinforcement — custom curricula, simulation exercises, and executive briefing packages.
IR plans, playbooks, and tabletop exercises covering detection, containment, eradication, recovery, and post-incident review — stress-tested through realistic simulation before a real event occurs.
Program architecture, tool selection, remediation prioritization frameworks, SLA development, and executive/board reporting that communicates risk in business terms — moving beyond scanning to operationalized risk reduction.
Audit preparation and execution across FISMA, SOX, HIPAA, SOC I/II, and NISPOM — gap assessments, evidence organization, and remediation guidance ahead of formal engagements.
CISO-level risk posture reporting, board presentation development, security strategy formulation, and interim CISO support — translating technical risk into executive language that drives informed decisions.
Before you build or buy AI, you need a strategy that aligns to your mission, your risk tolerance, and your people. ClearPoint Technology Services builds that foundation.
Phased AI adoption roadmaps aligned to mission and budget — AI maturity models, capability gap analyses, and prioritized investment recommendations aligned to EO 14110 and NIST AI RMF.
C-suite engagement to craft enterprise-wide AI strategies — AI vision statements, success metrics, and governance structures necessary to sustain AI programs long-term.
Structured assessments benchmarking readiness across data, infrastructure, talent, and culture — identifying specific gaps before programs launch so investment is not wasted.
Objective evaluation of custom development, COTS tools, and strategic partnerships — recommendations based on cost, risk, capability fit, and time-to-value to avoid costly misdirection.
Design and standup of internal AI CoEs — the hub for governance, best practices, tool standardization, and workforce enablement that accelerates adoption while maintaining quality control.
Responsible AI policies addressing bias, fairness, transparency, accountability, and human oversight — aligned to EU AI Act and OMB AI policy directives, positioned for evolving regulation.
Governance frameworks defining roles, approval workflows, documentation standards, and escalation procedures for all AI initiatives enterprise-wide — ensuring AI systems are deployed consistently, monitored continuously, and retired responsibly.
AI systems introduce risks that traditional security frameworks weren't built to address. ClearPoint Technology Services closes that gap with specialized AI risk and assurance services.
Comprehensive evaluations of AI systems for bias, fairness failures, explainability gaps, and unintended consequences — with prioritized risk registers and sector-specific mitigation recommendations.
Compliance services aligned to NIST AI RMF, EU AI Act, EO 14110, and agency-specific guidance from HHS, DoD, and DHS — mapping AI systems to requirements and identifying compliance gaps.
Independent assurance programs covering AI system performance, fairness, and governance — planning, evidence collection, control testing, and findings reporting for stakeholder confidence.
For AI systems affecting individuals — hiring, lending, benefits, law enforcement — systematic evaluation of potential harms, decision logic documentation, and safeguard recommendations.
Independent validation verifying model performance, bias controls, and fitness for intended use — documentation suitable for regulatory submission and leadership assurance programs.
Third-party AI product assessments covering security vulnerabilities, data privacy risks, bias exposure, and contractual accountability gaps — clear risk profiles before procurement or renewal.
AI-powered security operations that detect what signatures miss, respond faster than human-only teams, and harden the AI systems that adversaries will target.
Machine learning models integrated into security operations analyzing network traffic, endpoint telemetry, and log data in real time — surfacing anomalies and attack patterns for rapid analyst triage.
Behavioral baselines for users, devices, and applications that identify deviations indicating credential compromise, insider threat activity, or lateral movement — continuously learning as the environment evolves.
SOC augmentation with AI-driven automation that reduces analyst fatigue, prioritizes alert queues, and accelerates investigations — co-managed options extend capacity without proportional headcount growth.
AI-enhanced IR playbooks automating routine containment and remediation — isolating endpoints, revoking credentials, notifying stakeholders — dramatically reducing mean time to respond (MTTR).
Adversarial testing of ML models including data poisoning simulations, model inversion attacks, evasion testing, and prompt injection campaigns — identifying AI vulnerabilities before adversaries exploit them.
Structured assessments of LLM deployments covering prompt injection, indirect prompt injection, data exfiltration risks, and jailbreak vulnerabilities — with remediation guidance for AI application teams.
Detection capabilities identifying AI-generated synthetic media in corporate communications, identity verification workflows, and public-facing channels — addressing growing fraud and social engineering risks.
AI tools integrated into penetration testing to accelerate reconnaissance, vulnerability identification, and exploit chaining — more comprehensive coverage in less time.
Automated policy management, continuous control monitoring, AI-driven risk scoring, and intelligent evidence collection — reducing manual GRC burden while improving accuracy and timeliness.
Predictive models ranking vulnerabilities by likelihood of exploitation in your specific environment — enabling security teams to focus patching resources where risk is highest, ahead of threat actors.
From custom ML models to autonomous AI agents — ClearPoint Technology Services builds production AI systems tailored to your environment, your data, and your mission requirements.
Custom machine learning models for client-specific use cases — classification, regression, clustering, reinforcement learning — delivering production-ready models with full documentation and validation.
LLM fine-tuning on client domain-specific datasets — legal documents, technical manuals, internal policies — producing models that perform reliably within your domain and speak your organization's language.
Production RAG systems combining LLM power with real-time retrieval from your knowledge base — AI assistants that answer questions accurately using current, authoritative information rather than stale training data.
Single-agent and multi-agent systems orchestrating tasks across tools, APIs, and data sources — enabling automation of sophisticated business processes that go far beyond simple scripting.
Computer vision systems for object detection, image classification, document analysis, video analytics, and visual quality control — spanning security monitoring, identity verification, and document processing.
NLP pipelines for named entity recognition, sentiment analysis, document classification, and information extraction — unlocking value from unstructured text across contracts, reports, and regulatory filings.
AI-powered automation workflows connecting disparate systems, applying intelligent decision logic, and executing multi-step processes autonomously — reducing manual effort in operations, HR, finance, and compliance.
AI integration into existing enterprise systems via API orchestration and cloud AI platforms — Azure OpenAI, AWS Bedrock, Google Vertex AI — bridging AI capability and operational value without rip-and-replace.
AI that works in production — not just in demos. ClearPoint Technology Services builds the operational backbone that keeps models accurate, reliable, and secure at scale.
End-to-end ML pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, and monitoring — CI/CD practices for ML ensuring consistent, auditable production deployments.
Continuous model monitoring tracking performance metrics, detecting data and concept drift, and triggering retraining workflows — keeping AI systems accurate and reliable as the real world changes.
AI infrastructure on AWS, Azure, and Google Cloud — GPU compute clusters, managed ML platforms, and ML-optimized data pipelines — architected for scalability, cost efficiency, and security from day one.
For classified, sensitive, or compliance-constrained environments — fully on-premise or air-gapped AI deployments meeting FISMA, IL4/IL5, and DISA STIG requirements. No cloud dependency required.
Selection, configuration, and scaling of vector database infrastructure for semantic search and similarity retrieval — tailored to data volume and query performance requirements for RAG and AI applications.
Optimized AI models deployed to edge devices — sensors, cameras, mobile, embedded systems — for low-latency, limited-connectivity, or data sovereignty use cases using quantization and hardware acceleration.
AI that reduces operational burden, improves decision quality, and creates measurable efficiency gains across federal and commercial business functions.
IDP systems extracting, classifying, and validating information from unstructured documents — contracts, invoices, forms, reports — at scale using OCR, NLP, and ML to automate document-intensive workflows.
AI tools reviewing contracts for key clauses, obligations, risk provisions, and compliance requirements — reducing review time while improving consistency and reducing the risk of missed obligations.
ML-based fraud and anomaly detection for financial transactions, procurement activities, and claims processing — identifying suspicious patterns in real time to reduce losses and enable faster investigation.
BI platforms augmented with AI — natural language query interfaces, automated insight generation, anomaly highlighting, and predictive overlays — making data accessible and actionable for non-technical decision makers.
AI applied to federal acquisition workflows — opportunity identification, proposal analytics, market research automation, vendor performance monitoring — reducing administrative burden for contracting officers.
Structured feasibility studies and rapid PoC development that demonstrate technical viability and build stakeholder confidence before full-scale development investment is committed.
The most capable AI tools fail without an empowered workforce. ClearPoint Technology Services builds the human side of AI adoption — from literacy to advanced practitioner capability.
AI literacy programs for audiences from front-line staff to senior executives — building foundational understanding of how AI works, what it can and cannot do, and how to interact with AI tools effectively and responsibly. Customized by role and sector.
Hands-on workshops teaching staff to craft prompts producing accurate, useful, safe outputs — reducing AI errors and improving productivity across tools including Microsoft Copilot, ChatGPT, and Claude.
Structured adoption programs combining training, change management, and usage analytics to drive genuine uptake — ensuring organizations realize the value of their AI investments rather than leaving capability on the table.
Custom training curricula for organizations building internal AI capability at scale — from awareness modules to technical deep-dives — aligned to specific tools, use cases, and skill levels in instructor-led, self-paced, and blended formats.