Start with one problem. Finish with evidence.
Artheus is an applied AI and digital engineering firm in the Washington, D.C. metro area. We build for defense programs, federal agencies and industry. Every solution below runs on the Proof-First Lifecycle: you approve the test before we build, and nothing goes live until it passes. Each starts with a fixed-scope first step and ends with a deliverable you keep.
Evidence you can check, not a demo.
We prepare the evidence. The accountable person decides. Here is what that looks like.
Examples of the format, not client data.
Applied AI & Decision Support
A commander, a program manager or an operations lead has to decide with incomplete information and little time. AI can help only if the person can check what it says. Our assistants and agents answer only from sources you approve, show where each answer came from and send uncertain calls to a person. They run on your servers, in your private or government cloud, or disconnected at the edge, designed to fit the security authorization you already hold.
What we measure, agreed before we build: answer accuracy on a held-out test set you approve, citation accuracy (whether the cited passage supports the answer), and how often it correctly says the sources do not answer. Mapped to: NIST AI RMF 1.0 and NIST AI 600-1; for agencies, OMB M-25-21. Proof-First Lifecycle: all six stages.
Services
AI Readiness Sprint
A fixed-scope assessment that runs four to six weeks. We score candidate use cases on value, data readiness and risk. For agencies, we help determine which uses count as high-impact under OMB M-25-21. You get a ranked roadmap, a locked test set for the top use case, a first working build in your environment and a plain go or no-go.
Grounded Assistants and Agents
Assistants and agents that answer from your sources and cite the passage behind each answer, or say the sources do not cover it. Retrieval follows the source system's permissions and markings, so no one sees a passage they could not open. Agents get a least-privilege identity and approved tools only, stop for a person before changing a record and log every step.
Decision Support Analytics
We start from a named decision, its owner and its deadline, then work back to the data, forecasts and alerts that support it. The view shows the recommendation, the evidence behind it and what would change it. We record how the decision is made today, then measure time to decision and how often decisions are reversed against that baseline.
Digital Engineering
Plants, factories and defense programs run on facts buried in documents that do not always agree. When they disagree, the mistake can surface as rework on the shop floor or a delay during an outage. We turn those documents into an engineering model people can query, trace every element to its source and send every disagreement to an engineer to decide.
What we measure, agreed before we build: per-element accuracy (precision, recall and F1) against an answer key your engineers check, and elements traced to their source page. Mapped to: DoDI 5000.97 for defense programs; otherwise, the model format you use. Proof-First Lifecycle: every stage except Secure.
Services
Document-to-Model Conversion
Interface documents, bills of material, cable run sheets and port tables become a populated engineering model you can query. Every element carries the document, page and row it came from, and low-certainty elements are flagged for an engineer to check.
Provenance and Traceability Design
A design for how every model element resolves to its source and back (bidirectional traceability) and how requirements trace to their verification. Disagreements between documents are queued for a person to decide, never silently resolved. You get the data design and review rules your tools and engineers follow.
Digital Engineering Readiness Assessment
A fixed-scope look at the engineering data your program or plant still holds in documents. You get an inventory by document type and quality, a measured trial conversion on a slice of your own documents, and an estimate of what full conversion would take.
Conversion Quality Measurement
Before the work starts, your engineers help build an answer key (a gold set), and we agree the target with you. We then report precision, recall and F1 separately for each element type, plus the minutes it takes to correct each element.
We built and measured our document-to-model pipeline at our own expense on a synthetic test corpus (no controlled or classified material), made messy on purpose with 40 planted defects. It stands at technology readiness level 3. F1 is a standard accuracy score from 0 to 1 that counts both missed items and false finds. The corpus is synthetic and we built it, so these numbers show the method works; they do not predict how it will score on your documents. On an engagement, we measure on a sample of yours before agreeing a target. Cable connectors and requirements are our two strongest element types; others score lower, and the full scorecard is available on request.
AI Test & Assurance
An AI system is ready for a mission when someone accountable can see how it was tested and how it scored. Most AI arrives with a demonstration instead. We test AI you build or buy against a test set and pass mark locked before development starts, attack it the way an adversary would, and keep measuring it after launch. The result is evidence your authorizing official, safety board or Chief AI Officer can review; the decision stays theirs.
What we measure, agreed before we start: accuracy against the locked test set, how often the system correctly says it does not know, attack success rates under red-teaming, and drift after launch. Mapped to: NIST AI RMF 1.0 and NIST AI 600-1; the OWASP Top 10 for LLM Applications (2026) and MITRE ATLAS; for agencies, OMB M-25-21 and M-25-22. Proof-First Lifecycle: Assess, Prove, Secure and Operate.
Services
AI Test and Evaluation
Test, evaluation, verification and validation (TEVV) for AI you build or buy, against a test set and pass mark locked before development starts. We red-team for prompt injection and data leakage, mapped to the OWASP Top 10 for LLM Applications (2026) and MITRE ATLAS, and watch for drift. Model cards show a board or Chief AI Officer how it scored and where it falls short.
Secure AI and Red-Teaming
Models, prompts, retrieval indexes and agent tools treated as governed resources inside your zero trust architecture. Every agent gets its own identity and least-privilege tool access, prompts and responses are logged, and we record the source of every model and dataset. We test against the OWASP Top 10 for LLM Applications (2026) and for Agentic Applications, mapped to MITRE ATLAS.
Buying AI You Can Test
AI purchases an agency can defend in an audit. We help write requirements that carry test criteria agreed before award, rights to the data and the model outputs, and an off-ramp if the system does not perform. Each requirement is checked against OMB M-25-22 and, for large language model purchases, M-26-04. You get requirement language and a checklist your contracting team can reuse.
Training & Readiness
A signed training record proves someone attended. It does not prove they understood, and on safety-critical work, from a flight line to a plant floor, a misunderstood step can injure someone or ground the equipment. We build training that checks understanding at each critical step, in the person's own language, and keeps a record a supervisor can audit. For maintenance crews, the same assistants put the right page of the manual in front of them at the point of work, offline if needed, and cite it.
What we measure, agreed before we build: comprehension per procedure step (the share of people answering each check correctly) and time to competence by role. Mapped to: OSHA's Training Standards Policy Statement (2010) and Kirkpatrick Level 2 (what people learned). Proof-First Lifecycle: Assess, Build, Prove and Operate.
Services
FirstShift
Working prototypeOur working prototype: adaptive, multilingual AI that checks that frontline workers understand safety-critical procedures, in their own language. It is designed to ask about each critical step, re-teach on a miss and keep a record a supervisor can review.
Adaptive Onboarding
New hires ready sooner, without skipping what matters. A short check up front finds what each person already knows, so training spends its time on what they do not. Frontline and technical staff reach a set pass mark (a mastery threshold) before anyone signs them off, and you see time to competence by role.
Multilingual Training and Certification
Training and certification delivered in each worker's own language, with a record of what each person understood. A glossary reviewed by your safety lead keeps each safety term meaning the same thing in every language. You get certification records an auditor or inspector can check.
Immersive and XR Training
Practice for tasks that are unsafe or costly to rehearse on live equipment, such as a switching procedure or a line changeover. Staff rehearse the scenario in a headset (extended reality, or XR), and each step is scored. The record shows what each person can do before they touch the real equipment.
Maintenance Support at the Point of Work
The right page of the manual in front of the technician at the job. Answers come only from your technical manuals and maintenance records, cite the page and work order they came from, and say when the manuals do not cover the question. They run on your network or offline where there is no signal, and uncertain answers go to a supervisor instead of a guess.
Supporting work, on its own or alongside the above.
Security, data and wireless work that our AI and engineering programs depend on, offered as fixed-scope services in their own right.
Cybersecurity & CMMC Readiness
Security reviews stall on controls that exist on paper with no evidence behind them, and on plant control networks nobody dares to scan. A failed assessment can cost a contract, and a careless scan can trip a live process. We work from the assessor's side. Each control is written, with its evidence, against what your auditor, CISO or authorizing official will check, and every gap gets a dated fix.
What we measure, agreed before we build: assessment objectives met with evidence and zero trust maturity by pillar. Mapped to: NIST SP 800-171 Rev. 2 and 800-171A (CMMC, 32 CFR Part 170); NIST SP 800-207 and CISA ZTMM v2.0; NIST SP 800-82 Rev. 3. Proof-First Lifecycle: every stage except Connect.
Services
CMMC and NIST SP 800-171 Readiness
We scope the boundary around your controlled information and assess gaps against the 320 objectives in NIST SP 800-171A. You get a system security plan, fixes, a plan of action and milestones (POA&M) and help with your Supplier Performance Risk System (SPRS) entry and annual affirmation. As of October 2026, the certified third-party assessor (C3PAO) phase that was due on November 10, 2026 is suspended under DoD memoranda of July 13, 2026, while a DoD task force reviews the program; if it resumes, we will help you prepare.
Zero Trust Architecture (NIST SP 800-207)
A zero trust design built around your users, devices and data, starting with identity and phishing-resistant sign-in, in stages you can fund. We baseline you against the CISA Zero Trust Maturity Model v2.0 or, for DoD programs, the DoD Zero Trust Strategy's 91 target-level activities due by FY2027. You get a scored baseline for each pillar and a staged roadmap, re-scored after each stage.
Operational Technology Security
Protection for industrial control systems, SCADA and building systems, planned around uptime and safety. We start with passive asset discovery, so nothing on a live control network gets probed. Then we segment by the Purdue model and ISA/IEC 62443 zones and conduits, following NIST SP 800-82 Rev. 3. You get an asset inventory, a zone map and a staged plan your operators approve.
Before offering CMMC readiness to anyone, we took Artheus through the self-assessment path. We wrote a system security plan and gathered evidence for each NIST SP 800-171 Rev. 2 requirement. We posted a score of 110 of 110 in SPRS and affirmed CMMC Level 2 (Self) about two months after the company was formed. It is a self-assessment, not a third-party certification. Our CMMC readiness service walks you through the same path.
Data & Modernization
Rewriting a critical system all at once, whether it runs a factory's orders or an agency's benefits, risks the whole service on one cutover day. We modernize one function at a time, check the new against the old and keep a way back at each step. The same discipline gets data ready for AI: quality checks stop bad data before it reaches a model.
What we measure, agreed before we build: functions moved, new outputs matching the old, and data quality (completeness, timeliness and lineage). Mapped to: the controls your cloud already carries, from a company's baseline to an agency's FedRAMP or DoD impact-level authorization. Proof-First Lifecycle: all six stages.
Services
Incremental Modernization
Legacy systems retired piece by piece while the service keeps running. A stable interface goes in front of the old system, and functions move behind it one at a time (the strangler-fig pattern). Each move is checked against the old system's outputs before going live and can be rolled back. The old system retires only when the new one has carried the load.
Cloud Migration and Architecture
Architecture and migration on AWS, Azure and Google Cloud, including AWS GovCloud (US) and Azure Government. Landing zones, identity and infrastructure as code let every environment be rebuilt the same way. We design to inherit the controls your cloud already covers, so fewer are left for your own review. Cost guardrails go in up front, so the bill does not surprise finance.
Data Readiness and Pipelines
Data your analytics and AI can rely on, with problems caught at the source. We test your data against the questions it has to answer, scoring completeness, accuracy, timeliness, representativeness and traceability. Data contracts set what each source must deliver, and checks inside the pipeline hold back records that fail. You get pipelines, a readiness score for each source and a list of fixes.
Monitoring and Evaluation Platforms
Evidence a funder can check, for development programs and independent third-party monitoring. We design monitoring and evaluation systems around offline-first collection, so field teams can record where there is no signal. Each record is designed to carry a time stamp and a location, and indicators are tracked against the program's results framework. The design checks data for validity, integrity, precision, reliability and timeliness.
Spectrum & Wireless Networks
Plan, test and modernize wireless networks that have to share crowded spectrum and still work when the mission depends on them. We help organizations bring 5G and private wireless to bases, test ranges, ports, plants and campuses without interfering with the users already there, and prove each network performs before it scales.
What we measure, agreed before we start: coverage, speed and reliability against targets you set, and interference with neighboring users kept inside agreed limits. Mapped to: NTIA federal spectrum management rules and 3GPP 5G standards. Proof-First Lifecycle: Assess, Prove, Connect and Operate.
Services
Spectrum Sharing and Coexistence Analysis
Interference and coexistence studies that show how 5G and other wireless systems can operate alongside federal and commercial users, with the sharing rules and monitoring to keep it that way.
5G and Private Wireless Planning
Requirements, architecture, vendor evaluation and rollout plans for private 5G and LTE networks at bases, test ranges, ports, plants and campuses.
Wireless Test and Evaluation
Test plans, measurement campaigns and data analysis that prove coverage, speed and reliability before a network scales.
Network Modernization Roadmaps
Step-by-step plans to move legacy radio and wired networks to modern, secure architectures, including Zero Trust and satellite links.
Not sure where to start?
Tell us a little about what you are working on, commercial or government. We are happy to talk it through and suggest where we could help.