OperationsFeatured
Enterprise document search
Unified semantic search across policies, product and project documents, with answers that cite the source text and permissions that follow the user.
- Cross-industry
- Manufacturing
- Energy
From demo to production takes a whole delivery capability
Apolla pairs an enterprise AI platform with Forward Deployed Engineering (FDE) to take AI Agents from isolated pilots to stable production, and build them into a Digital Worker system that is measurable, manageable and keeps delivering business value.
- 79%
- of enterprises have adopted AI Agents to some degree
- 11%
- run them stably in production
- 5.1months
- median time for an Agent to deliver value
- 88%
- of production Agent deployments have had an incident
Sources: 2026 industry Agentic AI survey, Gartner
Industry reality
Nearly 80% of enterprises are piloting AI Agents; only about 10% run them in production
The gap between the two is where professional delivery capability earns its value. MIT NANDA research shows that 95% of generative AI pilots produce no measurable financial impact; Accenture observes that 80–85% of enterprises are stuck in the "PoC factory" stage. The problem is usually not the model but organization, data and engineering – the same use case can take 100× longer to deploy.
The platform standardizes capability; FDE closes the last mile
The two form a flywheel: the platform turns proven methods into reusable standard capabilities, while FDE works through the edge cases in the real business and feeds the lessons from each project back into the platform. Enterprise AI moves fast and stays stable.
ENTERPRISE AI PLATFORM
Enterprise AI platform
- One foundation with modular, composable Agent capabilities
- Multi-model orchestration, with the latest LLMs added continuously
- Standardized deployment with observability and governance
FORWARD DEPLOYED ENGINEERING
FDE professional services
- Experts on site, deep in the real business and data
- End-to-end ownership: from use-case discovery to production go-live
- Lessons from each project fed back into the platform
The platform makes it repeatable. FDE makes it work.
Six practice areas
A complete loop for enterprise AI transformation
From capability building and use-case deployment to organizational adoption, ongoing operations and closing the value loop – not a point tool, but a complete path.
AI Agent platform deployment
The technical foundation for enterprise AI · on-premises, controlled, manageable
Build an enterprise-grade AI platform so AI capabilities are managed, reused and scaled in one place.
Learn moreForward Deployed Engineering (FDE)
Forward Deployed Engineers · building with you, on site
Engineers work on site, with real data and production constraints, to take key use cases all the way to stable operation.
Learn moreIndustry Agent solutions
Agent packs built from delivered projects
24 curated templates, and growing, replicated fast by department and industry into a Digital Worker system.
Learn moreData governance and knowledge engineering
Turn enterprise knowledge and data into assets AI can use
Organize knowledge, data, processes and permissions to improve answer quality and business accuracy at the root.
Learn moreAgentOps managed operations
Go-live is not the finish line—it is where operations begin
Continuous monitoring, evaluation and optimization so your AI systems keep creating value over the long run.
Learn moreAI training and practice simulation
AI transformation is an organizational challenge, not just a technical one
Build a workforce that can, will and does use AI well, and raise adoption of the platform and Agents.
Learn more
Ready to use
24 curated Agent templates across eight functions, and growing
Project experience turned into products. Filter by department or industry, find the one closest to your use case, and reach MVP in 2–4 weeks.
OperationsFeatured
Deep research
Give it a research question and it breaks it into sub-questions, runs multiple rounds of internal and external retrieval, and delivers a structured report with citations.
- Cross-industry
- Financial services
- Professional services
Legal & complianceFeatured
Contract review
Checks contract clauses one by one against your own review checklist, flags risks with suggested edits, and produces a review memo.
- Cross-industry
- Manufacturing
- Professional services
Legal & complianceFeatured
Document compliance review
Reviews official documents, policies and external materials for format, content and compliance, pinpointing each issue with a suggested fix.
- Cross-industry
- Energy
- Financial services
FinanceFeatured
Invoice management
Recognizes, verifies and files invoices in bulk, matches them to contracts and payment orders automatically, and surfaces exceptions at a glance.
- Cross-industry
- Manufacturing
- Retail
FinanceFeatured
Excel data analysis
Ask Excel questions in plain language: it cleans, pivots, calculates metrics and produces charts and conclusions, with every step open to review.
- Cross-industry
- Retail
- Manufacturing
SalesFeatured
Sales assistant
Prepares customer background and interaction history before a visit, writes the follow-up notes and updates the CRM afterwards, so sales reps spend their time with customers.
- Cross-industry
- Manufacturing
- Professional services
Customer supportFeatured
Intelligent customer service
Answers customer questions from the product and service knowledge base, looks up orders, completes transactions and hands off to agents, measured on resolution rate rather than response rate.
- Retail
- Financial services
- Cross-industry
- Education
Case studies
Enterprise AI transformation, deployed for real
ChemicalsA specialty chemicals company
Technical inquiry response time from 3 days to 4 hours, technical service engineer capacity doubled
4hoursTechnical inquiry response time
ChemicalsA coatings company
Formulation development cycle down 30%, duplicate experiments down 40%
-30%Formulation development cycle
ChemicalsA large chemical company
Unplanned shutdowns down 45%, inspection record completeness at 99%
-45%Unplanned shutdowns
Three steps to start enterprise AI transformation
- 011–2 weeks
Diagnostic and alignment
An AI consulting workshop: analyze business processes in depth, identify high-value use cases, and define ROI and a roadmap
Deliverables
- Prioritized list of high-value use cases
- ROI estimate and transformation roadmap
- Platform and data readiness assessment
- 022–4 weeks
Flagship use case and validation
The FDE team works on site, building flagship use cases on real data and taking them to production
Deliverables
- Flagship use-case Agent live in production
- Evaluation set and benchmark report
- Platform deployment and system integration
- 03Ongoing
Scale and operate
Capabilities fed back into the platform, reused at scale, operated and optimized continuously
Deliverables
- Digital Worker system expanded quarter by quarter
- Monthly AgentOps operations report
- Training and an internal trainer pipeline
Start with an AI consulting workshop
In 1–2 weeks we work with your business team to map processes, identify high-value use cases, estimate ROI and deliver an actionable transformation roadmap. You do not need to know what you want to build first.