Evaluation suites, guardrails, proper engineering. Our customer service agent now resolves most queries end-to-end, rock-solid through peak seasons.
AI & Cloud
AI Harness & Governance
We build evaluation harnesses, security wrappers and governance frameworks that keep your AI models reliable, compliant and production-ready.
Engineered for high-pressure environments where one bad prompt deploy can become a compliance incident, and built to survive peak traffic, model upgrades and auditor scrutiny.
Promptfoo
DeepEval
LangSmith
Phoenix (Arize)
Datadog AI
EU AI Act mapped
Human approval logged
Release gate · prompt v4.2
Accuracy suite312 scenarios
PASS
Hallucination checkGrounded answers
PASS
Prompt injectionRed-team library
PASS
PII leakageOutput filter
REVIEW
1.2sp95 latency
0.4%Refusal drift
$0.8kDaily tokens
Trusted by businesses building for what’s next
Our Approach
AI Governance That Fits How Teams Actually Ship
Most AI failures aren’t model failures. They come from missing eval gates, unclear ownership and governance bolted on after launch.
01
Workflow-First Control Design
We map how prompts, tools and people interact in your real release process, then place harnesses where they stop bad deploys without slowing good ones.
- Release process mapped before tooling is chosen
- Gates placed at the highest-risk handoffs
02
Purpose-Driven Guardrails
Policies are coded to your data classes, risk tier and user journeys, not copied from a checklist. PII, jailbreak and topic rules match how your product is used.
- Rules versioned in code alongside each release
- Fewer false positives for real users
03
Analytics You Can Act On
Dashboards show quality, cost, latency and safety trends in business language, so leaders can see what changed after every model or prompt update.
- Release-over-release comparisons
- Alerts tied to owners, not inboxes
04
Growth-Ready Governance
Your architecture stays manageable as you add use cases, regions and models, so governance scales without becoming a bottleneck or a shadow IT project.
- Reusable controls across every new use case
- Clear ownership as teams grow
Overview
Control Frameworks for AI at Scale
Evaluation pipelines, guardrails and compliance oversight to run LLMs safely, from the first pilot through regulated production.
LLM Evaluation & Testing Harnesses
Automated evals for accuracy, latency, toxicity and hallucination, wired into CI so every model change is measured.
Enterprise AI Guardrails
Real-time input and output filters for prompt injection, toxic content, PII leaks and unauthorized data access.
Compliance & Audit Frameworks
Aligned with EU AI Act expectations, privacy law and internal risk policy, with evidence auditors can follow.
Human-in-the-Loop Workflows
Escalation paths where high-impact AI decisions are reviewed, approved and logged by human supervisors.
Services
Our AI Harness & Governance Services Include
Modular capabilities you can adopt as a full program or phase in by risk priority.
01
Regression Eval Pipelines
Scenario-based test suites in CI that run on every prompt, tool or model change, with pass/fail gates before production.
CI/CD · Quality
02
Runtime Guardrail Gateway
Input and output filtering for injections, toxicity and data leakage, with policy versions tied to each release.
Runtime · Security
03
Model & Prompt Registry
One source of truth for approved models, system prompts and rollback paths across every environment.
Versioning · Control
04
EU AI Act & Privacy Mapping
Control matrices linking each use case to the documentation, logging and human oversight it requires.
Compliance
05
Red-Team & Adversarial Evals
Scheduled attack libraries with findings tracked to remediation, aligned with your SOC and AppSec workflows.
Security testing
06
HITL Review Consoles
Queues where supervisors approve, edit or reject high-impact outputs, with a complete audit trail.
Human oversight
07
Drift & Quality Monitoring
Production scoring for hallucination rate, refusal patterns and user-reported failures over time.
Observability
08
Cost & Token Governance
Budget alerts, routing rules and model selection policies that keep AI spend predictable at scale.
FinOps
09
Platform Integration
Connect harnesses to LangSmith, Promptfoo, Datadog, Phoenix and your CI/CD, with no rip-and-replace.
IntegrationsWhy Teams Choose Us for AI Harness & Governance
We are engineers who ship production AI, not slide-deck strategists. Reliability, clarity and auditor-ready evidence are built into every engagement.
- Hands-on engineers from discovery to production
- Controls delivered as code, not documents
- Works with the tools your team already uses
15+
Years of combined platform and security engineering
50+
Production AI and cloud programs delivered
2
Global delivery hubs in the USA and India
24/7
Operational support options for critical systems
Shipping AI features without eval gates?
Get a 30-minute harness review and see exactly where untested changes can reach production.
Outcomes
What Teams Achieve With a Proper Harness
Measured results from teams that moved evals and guardrails into their release process.
70
Fewer production incidents from untested prompt changes
3
Faster release cycles with automated eval gates
100
Traceability for model versions, prompts and approvals
Days
Not months, to stand up governance baselines
Deliverables
Typical Deliverables
Concrete artifacts your security, legal and engineering teams can operate, not slide decks.
Eval Suite & Datasets
Regression datasets tied to real business scenarios.
Guardrail Policies in Code
PII, jailbreak and topic boundaries, versioned.
Observability Dashboards
Quality, cost and drift tracked in one view.
Risk Register & Control Map
Every AI use case mapped to its controls.
Red-Team Findings
Prioritized remediation backlog with owners.
Incident & Rollback Runbooks
Clear steps for on-call teams when quality drops.
Shipping AI features without eval gates?
Get a 30-minute harness review and see exactly where untested changes can reach production.
Case Studies
Governance That Works in Production
How we helped teams ship AI with measurable quality and audit-ready evidence.
Operations AI
Ops-Intelligence: Measurable Agents in Production
Eval suites and guardrails for agentic workflows, keeping automated actions within policy during traffic spikes.
View Case Study
Security
SecBoard: Audit-Ready Control Visibility
Governance patterns giving security and leadership one shared view of risks, controls and evidence.
View Case Study
Agentic AI
RunQuickSurvey: Feedback at Enterprise Scale
A harness for high-volume response data, keeping quality measurable across every channel the field team uses.
View Case Study
Business Models
Governance Across How You Go to Market
Controls differ for regulated B2B, high-volume B2C and direct digital brands. We tailor harness depth to your model.
B2B & Enterprise
Long sales cycles, role-based access and contractual security requirements. We emphasize documentation, segregation of duties and integration with your GRC tools.
Industries we support
Manufacturing
Healthcare & life sciences
Financial services
Software & IT services
Discuss Enterprise Needs
Shipping AI features without eval gates?
Get a 30-minute harness review and see exactly where untested changes can reach production.
Process
Our Proven Implementation Process
Six steps from first audit to continuous, automated governance.
-
01
AI Readiness & Risk Audit
Inventory models, data flows and regulatory exposure.
-
02
Governance Architecture
Define roles, policies and technical control points.
-
03
Harness Integration
Evals and guardrails wired into CI/CD and runtime.
-
04
Red-Teaming
Adversarial testing against real attack patterns.
-
05
Observability
Tracing, scoring and alerting in production.
-
06
Continuous Auditing
Scheduled evals, drift checks and governance reviews.
How We Engage
Maatara’s Governance Engagement Model
A clear delivery rhythm so you always know what’s shipping, who owns it and what comes next.
01
Analysis
Use-case inventory, risk tiering and success metrics for harness coverage.
02
Design
Policy architecture, data flows and tooling choices aligned to your stack.
03
Development
Evals, guardrails and integrations built with clean, testable code.
04
Optimization
Tune thresholds, reduce false positives and harden under load.
05
Deployment
Staged rollout, release gates and runbooks for on-call teams.
06
Support
Ongoing eval updates, model upgrades and governance reviews.
Shipping AI features without eval gates?
Get a 30-minute harness review and see exactly where untested changes can reach production.
Testimonials
What Our Clients Say
Hear from teams who needed production-grade AI, not demos.
They mapped our compliance gaps in the first workshop and shipped a harness we could show auditors within weeks.
Clear communication, no generic decks. Just engineers who integrated with our CI and observability stack.
Hiring Models
Flexible Engagement Models
Pick the model that matches your scope, timeline and internal capacity.
Dedicated Team
For multi-quarter governance programs.
- Engineers embedded on your roadmap
- Shared Slack, ceremonies and releases
- Scale the team up or down
Most popular
Fixed Scope
Baseline harness for one production use case.
- Defined deliverables and timeline
- Transparent, milestone-based pricing
- Clean handoff to your team
Advisory & Hourly
Expert help exactly when you need it.
- Architecture reviews and eval design
- Red-team sprints and audit prep
- Pay only for the hours you use
Shipping AI features without eval gates?
Get a 30-minute harness review and see exactly where untested changes can reach production.
Fit Check
Is AI Governance a Fit for You?
A quick check to see if an AI harness engagement makes sense right now.
A good fit if
- You ship LLM features to customers or internal users
- Legal or security needs evidence of AI controls
- Prompt changes currently bypass formal testing
- You use or plan tools like LangSmith, Promptfoo or Datadog
The wrong start if
- You only need a one-off chatbot demo with no production path
- There’s no access to logs, APIs or deployment environments
- Governance is deferred until after go-live
FAQs
Frequently Asked Questions
Quick answers on scope, frameworks and timelines. Cannot find yours? Ask our team directly.
Still have a question?
Ask an engineer, not a call centre. You get a straight answer within one business day.
Ask our teamRead access to how models are deployed and used: registries, deployment pipelines, the list of systems in production and whoever owns them. We can work from documents if access is limited, and we will say where that limits the work.
A register and a control matrix for the systems already running usually takes two to four weeks. Operating the controls takes longer, because it depends on how many use cases need human oversight and how your releases work today.
No. We map to the EU AI Act, the NIST AI Risk Management Framework and ISO/IEC 42001, and to whatever your clients ask for in a security or supplier questionnaire. The control set changes; the method does not.
It should not, and the controls are designed to prevent that. We place checks where risk actually changes and automate what can be automated, rather than adding a review meeting to every deployment.
Usually. We integrate with the registries, CI systems and GRC tools you run today, and we will tell you plainly when a control can only be met properly by changing one of them.
We do not give legal advice, sign off a certification on your behalf, or assess the risk of anything outside AI. We build the controls, the evidence and the workflows, and leave the legal call to your counsel.
Get started
Ready to Govern What You Already Run?
Tell us what is in production and who signs off on it. We will say what the gaps are and what to fix first.
Reply from an engineer within one business day
NDA available before we look at your stack
Fixed-price proposal, no hidden costs