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End-to-end technology services engineered for scale, from specialized engineering talent on demand to production AI and custom software delivery.
End-to-end technology services engineered for scale, from specialized engineering talent on demand to production AI and custom software delivery.
Autonomous Technical Sourcing & Assessment Infrastructure — Engagement Blueprint · Talent Operations (Tied to Hire Engineers)
Eliminates 80% of technical recruiting friction with multi-agent candidate discovery, automated GitHub repo code parsing, and interactive LLM technical screening rounds.
Technical hiring is bottlenecked by manual resume screening and non-technical recruiters. Engineering managers spend 15+ hours weekly reviewing misaligned CVs, conducting repetitive first-round tech screeners, and writing rejection notes. Sourcing teams rely on shallow keyword searches on LinkedIn that miss high-caliber passive engineers who build in public but maintain minimal social profiles.
Technical hiring is bottlenecked by manual resume screening and non-technical recruiters.
Engineering managers spend 15+ hours weekly reviewing misaligned CVs, conducting repetitive first-round tech screeners, and writing rejection notes.
Sourcing teams rely on shallow keyword searches on LinkedIn that miss high-caliber passive engineers who build in public but maintain minimal social profiles.
Legacy automations break under non-linear real-world enterprise edge cases.
Coordinated autonomous sub-agents executing specialized domain tasks under a deterministic supervisor state machine.
Consumes event streams, scores incoming payloads against deterministic policies, and dispatches tasks to specialized sub-agents.
Crawls open-source GitHub repositories, technical blogs, and papers to discover engineers by actual code quality rather than resume buzzwords.
Clones candidate pull requests, analyzes commit diffs, evaluates architecture patterns, and benchmarks clean-code practices in secure sandboxes.
Conducts structured 20-minute technical discovery chats, asking probing questions on distributed systems and debugging tradeoffs.
Compares candidate competencies directly against team hiring criteria, assigning calibrated match percentages and risk indicators.
Automates interview scheduling, answers technical questions about the role/stack, and ensures zero candidate ghosting.
Continuous Pipeline State Machine. Sourcing agents continuously populate an evaluation queue. The Code Evaluation agent executes sandbox analysis, passing verified candidates to the Screener Agent. Human engineering directors review scored candidate summaries before triggering live final-stage culture and team interviews.
Step-by-step event loop from inbound trigger to verified transactional completion.
Parses engineering hiring manager briefs, extracting tech stack constraints, seniority benchmarks, and core architectural responsibilities.
Searches GitHub commits, open-source contributors, and developer communities for engineers who actively write production code in the target stack.
Analyzes code maintainability, test coverage discipline, and algorithmic complexity across the candidate’s real repositories.
Engages the candidate with contextual technical questions exploring their real-world system architecture decisions.
Delivers a verified 1-page dossier with strengths, code samples, and salary expectation benchmarks directly into the hiring pipeline.
Production stack components configured for horizontal scalability, sub-second latency, and VPC data isolation.
A specialized autonomous talent intelligence engine integrated with your ATS and Git ecosystem. Includes automated screening agents, candidate scorecard templates, codebase evaluation sandboxes, and interview scheduling workflows configured for your engineering rubrics.
Complete containerized repositories with IaC Terraform/Helm scripts for private cloud deployment.
Deterministic test harnesses testing edge-case prompt responses, token costs, and safety guardrails.
Zero-drop state synchronization with HubSpot, Salesforce, Neno CRM, and ERP systems.
Multi-tier model fallback algorithms optimizing for response latency, cost, and task complexity.
OpenTelemetry distributed tracing, token consumption monitors, and audit logs.
Zero data retention by third parties with dedicated VPC hosting and encryption in transit/at rest.
Engineered to compress hiring manager screening time while maintaining strict engineering rigor.
Accurately evaluating code quality without falling for superficial vanity metrics like star counts or AI-generated resumes. We build AST (Abstract Syntax Tree) parsers and semantic diff analyzers that inspect actual engineering choices: exception handling discipline, modularity, test mocking depth, and concurrency safety.
Work directly with Neno Technology's forward-deployed engineering squads to scope, build, and deploy this blueprint inside your cloud environment.