solution partner

About Neol

Neol is an AI-native technology solutions company.  We work with government entities and strategic institutions to uncover high-impact opportunities hidden in their data, workflows, and mandates. Using our core technology platform, we build AI-native solutions that transform how teams search, analyze, and act on information, developed through structured discovery and rapid prototyping in our partners’ real operational context.

The Solution Partner sits at the center of Neol’s early-stage delivery and customer success funnel. This role is designed to bridge business development, solution scoping, delivery quality, and ongoing customer success.

The ideal Solution Partner is a structured, analytical, and client-facing operator who is comfortable navigating ambiguity and turning complexity into clarity. They enjoy being close to real customer problems, working across disciplines, and ensuring that good ideas become well-defined, deliverable solutions that actually create impact.

They are equally comfortable speaking with senior stakeholders, diving into operational details, and collaborating closely with product and engineering teams. They take ownership naturally, care deeply about quality and follow-through, and are motivated by seeing customers succeed over time.

Once initial BD conversations open the door and generate interest, the Solution Partner steps in to deeply understand the client’s real problems, map workflows, surface operational pain points, and analyze real data conditions. They validate needs and translate them into clear, actionable, AI-native pilot or project scopes, ensuring that the right projects are chosen, well-defined, feasible, and valuable. Working closely with the product and engineering teams, the Solution Partner anchors client expectations, prepares delivery-ready scopes, and ensures quality-controlled execution from the very start.

After the initial customization or pilot phase is completed, the Solution Partner becomes the primary point of contact for the customer. In this phase, they ensure successful adoption, monitor early impact, and support expansion into new use cases, teams, or workflows by building on proven outcomes. Throughout this process, the role continuously synthesizes insights across engagements, identifying repeatable patterns and opportunities that contribute to scalable solutions, reusable IP, and long-term customer success.

• Run structured discovery sessions with client teams, including interviews, role-by-role workflow walkthroughs, and process deep dives.
• Ask probing questions to uncover operational pain points, bottlenecks, data challenges, decision flows, and unmet needs.
• Conduct desktop research, benchmarking, and inspiration gathering to inform solution directions.
• Analyze current-state processes, data sources, tools, and organizational constraints.
• Capture insights in a clear, consistent structure that can be easily consumed by BD, product, engineering, and leadership.

• Identify themes and recurring problems across conversations and stakeholder groups.
• Transform raw notes, signals, and anecdotes into clear, structured problem statements.
• Distinguish between nice-to-have ideas and real, recurring, high-value problems.
• Formulate early hypotheses for solution directions grounded in feasibility and data realities.
• Produce concise Opportunity Summaries that help BD progress conversations with clarity and confidence.

Goal: Determine whether a real, valuable, and solvable problem exists.

Outputs:

• Clear articulation of the problem and its root causes
• Evidence that the problem is frequent, painful, and valuable to solve
• Alignment across stakeholders that the problem is worth addressing
• A clear go / no-go decision for progressing into pilot definition

Tasks:

• Consolidate discovery inputs into a unified diagnostic view.
• Validate assumptions through follow-up sessions or targeted clarification.
• Pressure-test problem statements against data availability, ownership, and organizational priorities.
• Ensure alignment between decision-makers, end-users, and technical stakeholders.
• Surface blockers early, including missing data, unclear ownership, or misaligned incentives.

Goal: Design a minimal, high-value AI-native pilot deliverable in 6 to 8 weeks.

Outputs:

• One-sentence Pilot Definition
• One-sentence Value Proposition
• Clear success criteria and measurable outcomes
• Detailed data access, integration, and dependency requirements
• A clean, structured handover package for engineering and delivery

Tasks:

• Translate validated problems into concise, outcome-driven pilot definitions.
• Define what success looks like jointly with the client, including impact, adoption, and metrics.
• Determine the smallest meaningful scope that delivers value while remaining feasible.
• Map required datasets, systems, stakeholders, and constraints.
• Ensure BD, engineering, and the client share the same expectations before delivery kickoff.

• Act as the owner of scope clarity and delivery readiness throughout the project lifecycle.
• Coordinate closely with engineering to support feasibility checks, sequencing, and trade-offs.
• Prepare documentation artifacts such as Problem Briefs, Pilot Scopes, Success Criteria, and Data Requirements.
• Support procurement, legal, security, and compliance discussions by providing early technical and scope clarity.
• Quality assurance: Ensure the ultimate product serves the goals and needs identified initially by generating test cases and testing the product extensively.  
• Grace period: Make sure the customer is properly onboarded to the solution and keep a very close eye on the initial adoption period to ensure feedback is flowing to the team and resolved quickly. 
• Serve as the connective tissue between BD, the client, and engineering from kickoff through stabilization.

• Act as the primary point of contact for assigned customers post-delivery.
• Conduct regular health checks and usage reviews to ensure sustained adoption.
• Support report requests, curation needs, and light communications or marketing enablement.
• Track usage patterns and surface insights back to product and BD teams.
• Lead onboarding for new users, features, or workflows.
• Identify and shape opportunities for expansion into new use cases, teams, or departments based on proven success.

Background & Experience

• Experience in roles such as solution consulting, digital transformation, engagement management, business analysis, product operations, or project management in a client-facing environment.
• Hands-on experience running discovery processes, scoping projects, or translating business problems into technical or product requirements.
• Familiarity with data-heavy, technology-driven, or AI-enabled solutions, even if not deeply technical themselves.
• Experience working across multiple stakeholders, functions, and levels of seniority.
• Exposure to managing or coordinating projects from early definition through delivery and stabilization.

Skills & Capabilities

• Strong problem analysis and synthesis skills; able to distill messy inputs into clear problem statements and actionable scopes.
• Excellent communication skills, both written and verbal, with the ability to create clear documentation and align diverse stakeholders.
• Solid project management instincts, including scoping, sequencing, risk identification, and dependency management.
• Ability to ask sharp, probing questions and challenge assumptions constructively.
• Comfort working with ambiguity, incomplete information, and evolving requirements.
• Strong collaboration skills and the ability to act as a bridge between business, product, engineering, and customers.

Ways of Working & Mindset

• Structured and detail-oriented, without losing sight of the bigger picture.
• Customer-obsessed, with a strong sense of ownership over outcomes and adoption.
• Calm, reliable, and proactive under pressure.
• Curious and continuously learning, especially around AI-native workflows, data, and emerging technologies.
• Values clarity, alignment, and long-term impact over quick wins.

• Client problems are clearly understood, validated, and aligned across stakeholders.
• Pilot and project scopes are crisp, feasible, and aligned with Neol’s capabilities.
• Engineering receives inputs that reduce ambiguity and accelerate delivery.
• Projects are well-managed from scoping through delivery and early adoption.
• Clients feel clarity, confidence, and momentum throughout the engagement.
• Conversion from discovery to pilot and from pilot to expansion increases.
• Neol builds repeatable, high-quality solutions anchored in real customer value.