iSpark Opens Its Full AI Services Practice With 148 Services and 14 Industry

[USA], 20 September 2026: iSpark, an AI consulting and engineering firm founded this year, has put its entire service catalogue online for anyone to read. The practice covers 16 service pillars and 148 services, supports 14 industry clusters and 12 business functions, and is delivered remotely. Pilots are scoped and priced before work starts, they aim to reach production in four to six weeks, and all intellectual property passes to the client on final payment.

Why iSpark decided to publish everything

Most AI pilots never make it to production. iSpark built its practice around that fact, and it says so plainly on its homepage. According to the firm, a convincing demo is easy to produce because the underlying models are now widely available. The hard part is everything that surrounds the model: testing, retrieval, guardrails, recovery plans and governance. Those pieces rarely show up in a sales presentation, so iSpark chose to document them in public.

The result is a site where every one of the 148 services has its own page, and so does every pillar, industry cluster and department. Engagement models, the delivery process and the firm’s contract commitments are all readable without booking a call or filling in a form.

The four problems the catalogue is built around

iSpark points to four repeat causes of stalled AI projects. Each one shapes how the services are organised.

• No evaluation harness. Teams release on gut feeling, then find quality drops in production with nothing to compare against.
• Retrieval treated as an afterthought. Output can never be better than what the system retrieves, yet many teams keep rewriting prompts when the real issue is how documents are split and indexed.
• Governance added too late. Risk classification gets squeezed in near the deadline, often after the legal team has already started asking questions.
• No way to roll back. Agents receive write access to live systems without a circuit breaker or a human checkpoint.

What the 16 service pillars cover

The first way to browse the catalogue is by capability, which suits technical buyers who already know what they need. Each pillar is a hub, and the services under it can be read and bought on their own.

• AI Strategy and Consulting: readiness audits, roadmaps and business cases built to hold up in front of a finance team.
• Generative AI and LLM Engineering: custom applications, retrieval systems and fine tuned models that work from the client’s own data.
• AI Agents and Agentic Automation: agents that finish tasks and leave an audit trail. This includes multi agent orchestration, Model Context Protocol servers that expose internal systems as safe tools, and AgentOps for tracing, cost control and rollback.
• Conversational AI: chat, voice and contact centre systems designed to resolve the problem, not push people to a form.
• Machine Learning and Predictive Analytics: forecasting, scoring and detection models judged against business results.
• Computer Vision: document reading, product inspection and real time video analysis, at the edge or in the cloud.
• Natural Language Processing: turning messy text into structured, searchable knowledge.
• Data Engineering and AI Readiness: pipelines, warehouses, vector stores and data cleaning, the groundwork every other pillar depends on.
• MLOps, LLMOps and AI Infrastructure: getting models live and keeping them observable, stable and affordable.
• AI Integration and Process Automation: connecting AI to the CRM, ERP and workflows teams already use.
• AI Governance, Security and Compliance: EU AI Act risk classification, ISO/IEC 42001 and NIST AI Risk Management Framework implementation, red teaming, prompt injection testing, bias audits, model cards and explainability documents.
• AI for Marketing and Growth: visibility in search engines and AI assistants, generative engine optimisation, personalisation and lead intelligence, with attribution a marketing lead can defend.
• AI Product and Experience Design: AI products people can trust, with humans kept in the loop wherever the stakes call for it.
• Creative and Media AI: image, video, voice and avatar production at brand consistent scale, with rights and provenance handled properly.
• Emerging and Frontier AI: physical AI, digital twins, AIoT and spatial computing for teams building ahead of the market.
• Managed AI Services and Talent: embedded engineers, retainers and rescue work for projects that stalled between pilot and production.

Two pillars take up most of the firm’s engineering time and published research: AI agents and AI governance. iSpark describes itself as a specialist first and a generalist second, and those two areas are where it has placed its bets.

14 industry clusters, because the sector sets the rules

The second way to browse is by industry. The reasoning is simple: a sector decides the data, the constraints and the regulator long before it decides the technology. The clusters are Healthcare and Life Sciences; Financial Services and Insurance; Retail and E-commerce; Manufacturing and Industrial; Technology and Telecom; Energy and Utilities; Transport and Logistics; Real Estate and Construction; Professional Services; Public Sector and Education; Media, Entertainment and Sports; Agriculture, Food and Environment; Travel and Hospitality; and Consumer and Lifestyle Services.

Each cluster splits into named verticals. Healthcare work includes clinical documentation, imaging, clinical trials and payer operations, built to withstand HIPAA and clinical validation. Financial services covers fraud, underwriting, KYC and advisory automation. Manufacturing covers visual inspection, predictive maintenance and shop floor intelligence at the edge. Public sector work covers citizen services, casework automation and learning systems where auditability is designed in from the start.

iSpark is also candid about what carries over from one sector to another. Engineering practice transfers completely, including evaluation, baselines, leakage checks, monitoring, drift detection, human review and cost per request. Process patterns transfer in part, since intake, dispatch, forecasting and inspection look similar everywhere but never share the same tolerances. Domain knowledge does not transfer, and the firm states that it belongs to the client.

12 entry points for teams that know the problem but not the technology

The third route is by department, for budget holders who can describe the pain without naming a solution. The twelve entry points are Sales, Marketing, Customer Service, Finance and Accounting, Human Resources, Legal and Compliance, Operations, Supply Chain and Procurement, IT and Engineering, Security and Risk, Product and R&D, and Executive and Strategy.

A five stage process where every stage has an exit

Work runs in five stages, and none of them obliges the client to commit to the next.

1. Diagnose (two weeks): an audit of data, systems and constraints, with a clear view of which use cases are viable now and which are not.
2. Prove (four to six weeks): one narrow pilot measured against a success threshold agreed before work begins.
3. Build: production engineering with evaluation, guardrails and observability included from the beginning.
4. Govern: model cards, risk assessments and the compliance documents auditors ask for.
5. Operate: monitoring, retraining and cost tuning on a retainer, or a clean handover to the client’s own team.

If a client stops after any stage, everything produced up to that point stays with them.

Four commitments in every contract

• A price before work starts. Diagnostics carry a fixed fee, pilots have fixed scope and fixed price, and nothing is quoted only on request.
• A target the firm can miss. Every pilot has a success measure agreed in advance. If it is missed, iSpark reports it as a miss.
• An exit at every stage.
• Full IP transfer. Prompts, evaluation sets, fine tuned weights and infrastructure as code all pass to the client on final payment.

iSpark says the second commitment is the one that changes its own behaviour most. Agreeing a number it could fail in front of a client, before any code is written, forces more careful scoping.

Free tools with no email required

Four working tools are available on the site without handing over contact details:

• AI Readiness Assessment: 24 questions scoring data, talent, governance and infrastructure maturity.
• AI ROI Calculator: estimates payback period and three year return from a company’s own headcount and volumes.
• EU AI Act Readiness Checklist: helps classify systems by risk tier.
• LLM Cost Estimator: compares inference costs across models and providers at a projected token volume.

The site also takes an unusual stance on social proof. Instead of a wall of client logos, it states that iSpark is new and will not pretend otherwise.

Availability and engagement models

iSpark works remotely, worldwide and in English, across all 16 pillars and 14 industry clusters. Clients can choose a fixed fee diagnostic, a fixed scope pilot, a milestone based build or a monthly retainer. Consultations last 30 minutes. The full catalogue is available at https://www.ispark.biz/.

About iSpark

iSpark is an AI consulting and engineering firm that designs, builds and governs AI systems for organisations around the world. Founded in 2026, it offers 16 service pillars and 148 services covering AI strategy, generative AI and LLM engineering, AI agents, conversational AI, machine learning, computer vision, natural language processing, data engineering, MLOps, process automation, AI governance, marketing, product design, creative AI, frontier AI and managed services. Work is delivered remotely across 14 industry clusters and aligned to the EU AI Act, ISO/IEC 42001 and the NIST AI Risk Management Framework. Engagements are fixed in scope, pilots reach production in four to six weeks after a two week diagnostic, and intellectual property transfers to the client in full on final payment.

Media Contact

iSpark
Email: hello@ispark.biz
Website: https://www.ispark.biz/

Published by CRECSO Blog.

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