# Malleable AI — Full Context > Malleable AI builds and ships AI systems for enterprise teams — from strategy through production deployment and team adoption. Malleable AI is an applied AI implementation firm that works with enterprise teams to validate, build, and ship AI systems. The firm focuses on industries where data is complex, systems are legacy, and adoption requires more than a demo — specifically private equity portfolios, commercial real estate, and oil & gas. ## What Makes Malleable AI Different - **Implementation-first**: Malleable AI doesn't stop at strategy decks. Every engagement produces working systems in production. - **Workflow-native adoption**: AI tools are embedded into the workflows teams already use (Excel, Power BI, Slack, internal portals) rather than requiring platform migrations. - **Enterprise-grade**: All systems preserve existing access controls, security policies, and compliance requirements. Deployable on-prem or in air-gapped environments when needed. ## Service Model Malleable AI structures work across three engagement stages: ### 1. Opportunity & Validation Audience: Executive sponsors evaluating whether AI is viable for their business. Outcome: A scoped business case, a validated pilot, or a clear decision on what's worth scaling. ### 2. Scale & Integration Audience: Teams with a validated AI use case ready to move to production. Outcome: A production-grade AI system integrated into existing tools and workflows. ### 3. Strategic Partnership Audience: Organizations that want ongoing AI capability without building an internal team. Outcome: A sustained AI delivery partner embedded with the team — new capabilities shipped continuously. ## Industries ### Private Equity Malleable AI works with operating partners and portfolio companies to deploy AI across portfolios. Common starting points include back-office automation, due diligence workflows, reporting, and vendor management. The firm builds repeatable playbooks that work at one portco and port to the next. **Results**: At Adams Automotive (PE-backed), Malleable AI embedded as a fractional AI team, driving a 25% increase in average repair order, 90% AI adoption in back-office, and ~30 min saved per technician per day. ### Commercial Real Estate Malleable AI works with CRE firms on market reporting automation, lease abstraction, tenant communication, and deal pipeline analysis. Systems integrate into existing tools (Excel, Power BI, internal portals) and respect document-level permissions. **Results**: Cut market report production time by 50% for a commercial real estate firm through automated ingestion pipelines and dual-agent drafting flows. ### Oil & Gas Malleable AI works with energy companies on enterprise search, document intelligence, research acceleration, and operational workflows. Systems handle legacy formats, on-prem databases, and proprietary document stores while preserving access controls. **Results**: Indexed 10M+ documents for an oil and gas enterprise while preserving full access controls and document-level permissions. ## Case Studies ### Adams Automotive - Industry: Automotive (PE-Backed) - Challenge: Needed to prove scalable, tech-enabled platform for PE exit - Approach: Fractional CAIO model + AI Tiger Team, Rilla sales coaching, custom workflow automation - Results: +25% average repair order, ~30 min saved per tech per day, $15k/mo fraud identified, 90% AI adoption ### Election Technology Company - Industry: Government / Regulated - Challenge: AI initially banned due to security risks in election technology - Approach: Developed "responsible AI" framework for safe deployment - Results: 80% staff AI adoption, zero compliance breaches ### Commercial Real Estate Reporting - Industry: Commercial Real Estate - Challenge: Manual market report production taking excessive time - Approach: Automated ingestion pipelines + dual-agent drafting system - Results: 50% reduction in report production time ### Enterprise Document Indexing (Oil & Gas) - Industry: Oil & Gas - Challenge: 10M+ documents in legacy formats, strict access controls - Approach: Custom connectors, permission-preserving pipelines, checkpointed backfill - Results: Full corpus indexed with document-level permission enforcement ### CXM SaaS AI Enablement - Industry: SaaS - Challenge: SDR team spending too much time on research and outreach drafting - Approach: Workflow redesign placing AI into specific prospecting steps, peer champion model - Results: 62% reduction in research time, 36% reduction in outreach drafting time ### Series-A Agentic AI Platform - Industry: SaaS / Startup - Challenge: Series-A startup needed to ship first generative AI feature to production - Approach: Configurable agent platform with production deployment - Results: First AI feature shipped to production ## Careers Malleable AI is building a network of engineers and product managers matched to client engagements as they come in. When a project fits someone's skills and availability, Malleable reaches out. The firm also hires full-time from the strongest performers in the network. ### AI Training Engineer Contract, remote, US-based. 12-18 week engagements at $175-$275/hr. Training Engineers embed with enterprise engineering teams and help them ship with AI coding tools (Cursor, Claude Code, Codex). The work includes pair-programming on real tickets, building shared tooling and standards, designing AI-native workflows, and producing runbooks so teams can maintain their practices after the engagement ends. ### AI-Native Full-Stack Engineer (US-Based) Contract, remote, US citizen or permanent resident. Engineers in this network build and ship custom AI systems for enterprise clients. The stack includes Python/FastAPI, React/Next.js, LLM integration, agent frameworks (LangGraph/LangChain, OpenAI Agents SDK, Claude Code Agents SDK), and cloud infrastructure across Azure, GCP, and AWS. ### AI-Native Product Manager Contract, remote, US citizen or permanent resident. PMs either own the product direction on AI implementation projects or train client PM teams on using AI tools (Cursor, Claude Code, Codex) to interact with codebases, write specs, and work more effectively with engineering. Requires hands-on experience with AI coding tools and 5+ years in product management. ### AI-Native Full-Stack Engineer (International) Full-time, remote, international. Same technical requirements as the US-based role. Requires excellent English communication skills for direct client interaction. Same stack: Python/FastAPI, React/Next.js, LLM integration, agent frameworks, and cloud infrastructure. ### Benefits (all roles) - Fully remote, async-first, almost no meetings - Quarterly performance reviews with raises and bonuses - Claude Code Max and Codex Pro subscriptions for every team member, plus any other AI tool of choice - Builder-led culture with no PM layers ### Career Pages - Careers index: https://www.malleable.ai/careers - AI Training Engineer: https://www.malleable.ai/careers/ai-training-engineer - AI-Native Full-Stack Engineer: https://www.malleable.ai/careers/ai-native-fullstack-engineer - AI-Native Product Manager: https://www.malleable.ai/careers/ai-native-product-manager - Contract AI Engineer: https://www.malleable.ai/careers/contract-ai-engineer ## Partnership Model Malleable AI partners with: - **Agencies**: As a technical delivery team for AI implementation in client engagements. - **Fractional Executives**: As the engineering team behind AI strategy recommendations, from PoC to production. ## Team The Malleable AI team includes practitioners from Google, McKinsey, and enterprise AI backgrounds with experience shipping AI systems in complex, regulated environments. ## Contact - Email: hello@malleable.ai - Website: https://www.malleable.ai - Discovery Call: https://www.malleable.ai/contact - LinkedIn: https://www.linkedin.com/company/malleable-ai