Nov 18, 2025
What if you could cut a week of frantic quoting down to a few short hours, without changing the tools your team already uses? You can. Many contract manufacturers still spend 7 to 10 days re-drawing harnesses, parsing PDFs, and chasing supplier prices. That is where Cableteque’s cloud solution, Quoteque, comes in: an AI-powered, domain-aware quoting platform that can take that weeks-long scramble and make it a minutes-long, precise process, while fitting into your existing workflows and supplier relationships.
Small changes, done deliberately, compound into dramatic improvement. By automating BOM extraction, codifying simple sourcing rules, and collecting modest amounts of labor data, you free engineers from repetitive tasks, tighten margins, and win more bids. You do not need a rip-and-replace of ERP or CAD systems to do it. With Quoteque you keep your firm’s supplier rules, vendor approvals, and customer-specific part mappings, while reducing the initial quote assembly time from 7 to 10 days to about 30 minutes in many pilots.
Table of contents
The quoting dilemma for contract manufacturers
How Quoteque solves the problem
Compounding actions: small steps that multiply
Why this approach does not disrupt workflows
Measurable outcomes and a simple implementation roadmap
The quoting dilemma for contract manufacturers
You know the scene. An OEM sends a PDF, sometimes a stack of PDFs. Engineers need to recreate wiring topology, match customer part numbers to manufacturer part numbers, calculate wire lengths, and find reliable suppliers. Each of those steps invites delay and error. When quotes take a week or more, opportunities slip away and margins shrink. In many operations the success rate for complex quotes can feel like a coin flip, because manual steps create variance and risk.
The business impact is concrete. Long cycle times mean missed bid windows. Inconsistent pricing means lost contracts or margin erosion. Engineers who could be solving technical problems spend their time transcribing parts lists and chasing cross references. That is expensive and low value. You need accuracy and speed, but not chaos. You want precision without disrupting the way your people and systems work.
How Quoteque solves the problem
Quoteque was built around that tension, to improve quoting precision and speed without forcing a rip-and-replace of your stack. The platform automates the front end of quoting, using domain-aware AI, a large parts database, and live supplier feeds to turn unstructured design data into an accurate, sourced quote quickly.
Quoteque can extract BOMs and wiring topology from OEM PDFs in minutes. It uses a parts database of more than 2,000,000 parts, and applies rules to map customer parts to manufacturer part numbers, suggest alternates, and standardize packaging and reel conversions. It pulls real-time supplier pricing so your cost assumptions reflect current lead times and availability. Those combined capabilities let you present tighter, more competitive quotes faster.
If you want to see the industry adopting this approach, note that Electrical Components International announced a partnership to embed Cableteque into quoting and product development workflows, with a focus on automatically generating BOMs from customer design data. Read the ECI announcement at ECI partners with Cableteque to transform harness quoting with automation to see how a distribution leader frames the value.
You should also know that Quoteque fits into broader digital threads. Partners such as Zuken are integrating design and quoting workflows to reduce handoffs and errors. A detailed take on that integration appears at Accelerating wire harness design, quoting, and manufacturing with digital thread integration, which illustrates how connecting data end-to-end eliminates manual transcription points.
Compounding actions: small steps that multiply
You want rapid, measurable gains. The best path is not a big bang. It is a series of small, practical actions that stack up over time. Here are four actions you can start today. Each one is manageable, and each one multiplies the benefits of the others. Taken together, they convert occasional successes into a sustainable, efficient quoting engine.
Action 1: Automate pdf extraction and standardize boms
Start by automating the most tedious, error-prone task, turning PDF BOMs and drawings into structured data. Drag-and-drop import, automated text extraction, and topology tracing cut the hours of manual recreation. In practice, teams that adopt automated extraction report reductions in BOM recreation effort by up to 96% on the items processed.
Why start here? Because you free up engineering time immediately. You reduce transcription errors, and you make the rest of the quoting process deterministic. When the BOM is consistent and machine-readable, everything else becomes simpler. You can validate quantities, compare alternatives, and calculate wire lengths without manual measurement.
A true-to-life example: a contract manufacturer that used to take 7 to 10 days to assemble a detailed quote ran a pilot importing 10 typical PDF jobs through automated extraction. The pilot found the initial assembly time fell to about 30 minutes for the same scope. The work did not require retooling CAD systems or changing ERP processes. You can read more about similar transformations in Cableteque’s blog post describing how firms moved from 10 days to 30 minutes at Transform your wire harness quoting process from 10 days to 30 minutes with Cableteque.
Practical tip: when you run your first pilot, pick a mix of simple and complex jobs so the model encounters edge cases. That helps you tune validation rules and identify any ambiguous part lines that need human review.
Action 2: Apply simple sourcing rules and alternates
Once you have a standardized BOM, apply simple sourcing rules. Capture your preferred vendors, packing preferences, and approved alternates in a small rule set. The platform will autopick compatible terminals and seals, suggest packaging conversions, and surface alternate MPNs that meet your test and approval criteria.
This action pays off fast. Instead of spending days contacting five distributors, you get instant price and lead-time visibility. When supplier feeds are live, dynamic costing updates the quote as availability changes, so your estimates stay current up to the moment you send them. That real-time sourcing reduces the number of late surprises and rework requests after a quote is accepted.
Cableteque’s sourcing engine demonstrates this behavior. The platform picks missing components based on connector compatibility and wire gauge, then fetches live supplier pricing. See how that model reduces uncertainty in day-to-day quoting in the Cableteque article on AI-driven quoting at Eliminating guesswork, AI revolutionizes wire harness quoting.
Practical tip: start with three to five vendor preferences for your pilot product line. That keeps the sourcing rules focused and ensures costing behavior matches procurement policy.
Action 3: Capture labor estimates and reuse tribal knowledge
Labor estimation is another place where small habits compound. Start tracking assembly times on quotes and projects, and feed that data back into your quoting engine. Even crude historical averages beat ad hoc guesses. Over time, your labor model becomes more accurate and requires less override work from senior engineers.
You do not need to make a precise model on day one. Capture a few categories, such as connector assembly, wire cut-terminate, and bundle operations. Let the software learn from completed jobs and recommended times. The cumulative effect is that your labor estimates improve with each job, and you liberate engineers from low-value estimation decisions.
This is also how you preserve institutional knowledge. The platform codifies tribal rules, like customer-specific part mappings and preferred alternates, so a new estimator does not need to rebuild that knowledge base from scratch.
Practical tip: display suggested labor times prominently during quote review so reviewers can accept or adjust them quickly. The marginal time spent validating a suggestion is far lower than creating an estimate from scratch.
Action 4: Integrate incrementally with existing systems
Integration should be incremental. Start with PDFs, then add a single supplier feed, and then link to one ERP or CAD system for quick wins. This approach keeps risk low, and it means you do not force the team into a new workflow overnight. Instead, you add capabilities where they produce the most value.
For example, begin by exporting the standardized BOM into an ERP import template you already use. Then add a tight link to your CAD tool for jobs where you want a synchronized topology. The goal is to augment, not to replace. Incremental adoption preserves supplier rules and customer relationships, while delivering the automation you need.
Practical tip: choose an export format that your ERP team accepts without modification. Early wins create internal champions who will advocate for broader adoption.
Why this approach does not disrupt workflows
Non-disruption is a promise you can keep if you design for it. Cloud-based platforms like Quoteque allow teams to keep their ERP, PLM, and CAD tools. You add a layer that extracts, standardizes, and enriches data, and then pushes validated outputs back into your systems.
Key elements that prevent disruption:
Start small and prove accuracy with a pilot.
Map customer-part numbers to MPNs, preserving legacy relationships.
Maintain manual approval gates for senior engineers.
Configure the sourcing engine to respect approved vendors and source preferences.
That design philosophy is why distributors and partners are choosing to embed these capabilities into existing workflows. The ECI partnership highlights how embedding automated BOM generation supports quoting and product development without replacing legacy systems. See the ECI announcement at ECI partners with Cableteque to transform harness quoting with automation for that perspective.
In short, you gain speed and precision without forcing a cultural reset. Engineers keep their judgment, procurement keeps its vendor rules, and sales gets a faster, more reliable quote delivery cadence.
Measurable outcomes and a simple implementation roadmap
You want clear metrics. Here are outcomes you can expect, based on industry experience and pilot projects.
Quoting cycle time, from 7 to 10 days down to 30 minutes for initial BOM assembly in many pilots.
Manual BOM recreation, reductions up to 96% for extracted items.
Overall process time, typical reductions up to 50% across the quoting lifecycle, due to fewer handoffs and faster sourcing.
Parts database, access to more than 2,000,000 parts for automated mapping and alternates.
A simple roadmap to scale:
Proof of concept, using a representative set of PDF BOMs to verify extraction accuracy.
Load customer mappings, preferred vendor lists, and packaging rules.
Pilot with one supplier feed and one product line, capture labor data.
Expand supplier integrations and connect to ERP/CAD systems as needed.
The roadmap keeps risk and cost low. You can measure outcomes at each stage and tune the model as you go. Expect early wins in the pilot phase that justify phased expansion, and use those wins to build internal momentum.
Key takeaways
Automate the low-value tasks first: start with PDF BOM extraction to cut manual recreation by up to 96%.
Codify sourcing preferences: small rule sets for preferred vendors and alternates deliver immediate pricing accuracy.
Build labor models incrementally: capture simple categories and let the system refine estimates over time.
Integrate in steps: connect supplier feeds and ERP or CAD systems only after a validated pilot.
Measure and scale: use pilots to prove ROI, then expand to more product lines and suppliers.
FAQ
Q: How accurate is automated pdf extraction for complex harnesses?
A: Automated extraction is highly effective for structured data, and domain-aware AI reduces errors on ambiguous items. In practice, the platform captures the majority of BOM lines automatically, while surfacing uncertain items for quick manual validation. You should expect a significant reduction in manual transcription, even if some edge cases still need human review. Run a short proof of concept on representative jobs to validate accuracy for your product mix.
Q: Will integrating Quoteque force us to change our erp or cad tools?
A: No, the platform is designed to augment, not replace, your existing systems. You can start by exporting standardized BOMs in the formats your ERP expects, then add tighter links to CAD or PLM tools if you choose. Incremental integration keeps risk and training costs low, and it lets you preserve existing supplier relationships and approval workflows.
Q: How does supplier pricing stay current in the quote?
A: Quoteque connects to live supplier feeds to pull pricing and lead-time information at the time you assemble the quote. You can configure approved vendors and preferred sources so the sourcing engine respects corporate purchasing rules. Dynamic costing updates the quote as availability changes, reducing the chance of price surprises after acceptance.
Q: How quickly will engineers see time savings?
A: You will see immediate gains from automating BOM extraction, often within the first pilot. That reduces manual transcription and frees senior engineers from repetitive review tasks. Additional savings accrue as you capture labor times and apply sourcing rules, because those changes compound and reduce rework over many quotes.
Q: Is the ai domain-aware for wire harness specifics?
A: Yes, Quoteque applies domain-specific heuristics for parts like terminals, seals, and cable assemblies. It understands common shorthand and packaging conversions, and it uses a parts database with more than 2,000,000 entries to map customer parts to manufacturer numbers. That domain focus improves accuracy compared to generic document parsers.
Q: What are reasonable goals for a pilot?
A: Aim to validate extraction accuracy and sourcing logic on a set of typical jobs, then measure time saved per quote and error reductions. A good pilot will also test one supplier feed and export into your ERP. Use those metrics to calculate ROI and plan wider rollout.
About Cableteque
Cableteque combines over three decades of hands-on industry expertise with a commitment to innovation in wire harness software. Founded by Arik Vrobel, our team brings together engineers, operators, and business leaders who deeply understand the challenges related to wire harnesses.
We focus on solving the toughest problems across the entire design-through-manufacturing lifecycle, helping teams work smarter, faster, and with greater precision.
Our company thrives on innovation, inclusivity, and collaboration. We value individuality, sustainability, and making a positive impact, building trust and shared success every step of the way. We are the only company creating software designed by wire harness people, for wire harness people. Our goal is to simplify communication between OEMs and contract manufacturers, streamline operations, and help businesses grow.
Cableteque isn’t just a tool, it’s an evolving platform built to empower engineers, supply chain specialists, sales teams, and manufacturing professionals to do their best work. Our company thrives on innovation, inclusivity, and collaboration.
