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Design AI assistants, agents, knowledge systems, and workflow intelligence around real organizational processes.
Moving beyond chat interfaces requires engineering reliable, task-oriented agents that execute multi-step operations within defined organizational guardrails. Evergreen designs deterministic agent architectures that combine context, validated tools, granular permissions, finite-state orchestration, continuous evaluation, and human oversight to automate complex operational workflows without unpredictable behaviors.
We focus on solving concrete engineering, data, and organizational bottlenecks rather than speculative generative AI hype.
General-purpose generative models generate plausible-sounding inaccuracies when queried about internal company procedures, pricing tables, or technical manuals.
Ad-hoc multi-step prompts break unpredictably when upstream data schemas change, downstream APIs return edge-case errors, or context lengths expand.
Autonomous agent prototypes risk infinite execution loops, unauthorized record modifications, runaway API spend, or unintended tool invocations.
Organizations cannot explain or verify why an AI agent selected a specific tool, filtered a dataset, or recommended an action during compliance audits.
Valuable enterprise data sits isolated in ticketing systems, databases, and ERPs that AI models cannot interact with securely or reliably.
AI agents that follow strict state transitions, validate inputs and outputs against schemas, and halt safely upon encountering anomalous states.
Automated routing that executes read-only analysis autonomously while escalating high-risk write, delete, or financial operations for human approval.
Step-by-step audit logs capturing prompt versions, context snapshots, tool API payloads, and execution latency for every agent run.
Agents equipped with short-lived, scoped credentials ensuring they cannot access or modify systems outside their operational domain.
Decoupled orchestration layers capable of switching between leading commercial frontier models and self-hosted open-weights engines.
Evergreen rejects the premise of unconstrained autonomous agents. We engineer agentic workflows as finite-state machines where every tool invocation, data transition, and state mutation is subject to strict policy enforcement.
Reliable Agentic AI = Context + Tools + Permissions + Orchestration + Evaluation + Governance + Human Oversight.
Structuring agent workflows with defined states, transitions, timeout caps, and loop limits rather than open-ended recursive loops.
Executing agent-generated code, SQL queries, and tool APIs in isolated, containerized environments designed with controlled external transmission paths and restricted network egress.
Integrating asynchronous approval gates for any action that affects financial ledgers, customer records, or critical infrastructure.
Every client engagement produces tangible architectural artifacts, verifiable codebases, or defensible strategic roadmaps.
Custom conversational systems grounded in private corporate knowledge with strict citation provenance and role-based access control.
Specialized agents engineered to accomplish specific operational workflows such as document reconciliation, triage, or structured extraction.
Robust graph controllers managing multi-agent collaboration, state checkpoints, error recovery, and conditional branching.
Bridging AI agents to enterprise ERP, CRM, and database endpoints using strongly-typed OpenAPI contracts and parameter validation.
Interactive approval dashboards, webhook notifications, and escalation consoles that pause execution until authorized personnel sign off.
Automated benchmark test suites that stress-test agent reasoning, tool accuracy, adversarial prompt injection resilience, and drift.
Hybrid routing layers that dynamically route tasks to the most cost-effective, lowest-latency model matching the task's complexity.
Deterministic architectures enforcing data perimeter containment, least-privilege tool execution, and clear trust boundaries.
Finite-state machine control loop with policy validation and human approval intercept.
Receives objective, parses context, and initializes execution graph state.
Emits proposed action JSON conforming to strict OpenAPI schema contracts.
Validates payload parameters, checks rate limits, and scores operational risk.
Suspends graph execution if action modifies external production state.
Executes call within ephemeral container and returns sanitized result to agent.
Informed by the NIST AI Risk Management Framework (GOVERN and MAP functions), OWASP Top 10 for LLMs, and zero-trust architectural principles.
Enforced Validation Controls:Autonomous agents are deployed with strict human-in-the-loop gates. Evergreen does not deploy unconstrained or fully autonomous write-access agents in production environments.
Strictly classified in accordance with Evergreen's published claim-governance rules.
Context: Evergreen engineered an open reference blueprint detailing finite-state machine transitions, ephemeral container sandboxes, and human-in-the-loop gates.
Approach: Utilizes graph state controllers, Pydantic tool validation, and asynchronous approval webhooks to prevent infinite loops and invalid API mutations.
Outcome / Spec: Reference architecture blueprint published in the Evergreen technical library for enterprise implementation.
Context: A national mortgage and securities processing network sought to automate unstructured document indexing while adhering to strict consumer privacy mandates.
Approach: Architected client-side data masking middleware and automated document classification pipelines with executive policy sign-off.
Outcome / Spec: Intercepted sensitive identifiers prior to external model routing and accelerated loan turnaround across pilot branch offices.
Initiate a confidential technical consultation with our engineering and strategy team. All inquiries are routed directly to Senior Principal Dr. Felix Njeh and our technical architecture practice.
Confidential intake • Zero client data used for model training • Austin, Texas • Nationwide Enterprise & Public Sector Deployments