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Fix RAG pipeline issues — without re-launching your site

LLM apps that ground answers, control cost, and pass evals

  • Senior engineers · IST + EST overlap
  • NDA on day 1
  • 24-hour reply

Tell us what you need fixed

Reply in 24 hours · NDA on day 1 · No spam.

What you're seeing

Your RAG chatbot misses obvious answers, retrieves wrong chunks, or cites stale documents.

Our approach

We rebuild the ingestion (chunking, embeddings, re-ranking), add retrieval evaluation, and fix the chunking strategy until the top-k carries the actual answer.

Symptoms teams come to us with

  • The model confidently invents facts and fake citations
  • You ship LLM changes by vibes, with no eval to catch regressions
  • API bills are climbing and finance wants a plan
  • RAG retrieves the wrong chunks or stale documents

What we get right

  1. Retrieval grounding and citation-required prompting
  2. A scored eval harness wired into CI before changes ship
  3. Model routing, caching and batching to cut token spend
  4. Chunking, embeddings and re-ranking tuned for recall

Concrete deliverables, no fluff

Every engagement ends with measurable, documented outcomes — no black-box agency reports.

  • Evaluation harness with scored test cases
  • Implementation behind feature flags + rollback plan
  • Cost & latency dashboard wired to your observability
  • Hand-off doc covering prompts, models, and guardrails

From brief to shipped fix

A transparent, low-risk process — a senior engineer reads your brief personally, and nothing starts until you approve a written plan and price.

  1. 01Day 0–1

    Diagnose

    A senior engineer reviews your brief, reproduces the issue, and pinpoints the real root cause — not the symptom — before any code is touched.

  2. 02Within 24h

    Scoped plan & quote

    You get a written plan to fix RAG Pipeline Issues, a firm timeline, and a fixed quote. Nothing starts until you approve it — no surprise invoices.

  3. 032–6 weeks

    Ship the fix

    We implement on a branch and open a pull request you review, working to your code-review standards on your repo — never a black box.

  4. 04On delivery

    Verify & hand off

    We verify on staging and production, share before/after evidence where it applies, and leave you a short hand-off note so the fix sticks.

Why teams hand this task to Krapton

  • Senior engineers only

    Your brief is read and handled by a senior engineer — no junior hand-off, no sales-rep filter in between.

  • Root cause, not a patch

    We reproduce and fix the underlying cause, then add a guard so the same class of issue does not quietly return.

  • Your repo, your standards

    Every change lands as a pull request you review, on your repository, following your existing review process.

  • NDA on day one

    Confidentiality and IP are covered before we look at a single line of code. All work stays in your accounts.

  • Fixed quote up front

    You approve a written plan and price before work starts. If scope changes, we re-quote in writing — no surprise invoices.

  • Proof, where it applies

    Performance, SEO and reliability work ships with before/after evidence so the result is measurable, not anecdotal.

Three ways to engage

No retainer required. Pick the model that matches the work — pricing for this task starts from $3,500, with a fixed quote before anything starts.

  • Per task

    Most popular

    One clearly-scoped fix at a fixed price. Best when you know exactly what is broken and want it handled end to end.

    • Fixed quote up front
    • One PR, reviewed by you
    • No retainer required
  • Hourly

    Pay only for the hours worked. Best for diagnostics, audits, or exploratory work where the scope is still emerging.

    • Weekly timesheets
    • Pay for what you use
    • No minimum commitment
  • Per sprint

    A focused 1–2 week sprint when the work is bigger than one fix but smaller than a full project.

    • 1–2 week blocks
    • Clear sprint goal
    • Scale up or stop anytime

Industry-standard stack, no proprietary lock-in

  • OpenAI
  • Anthropic Claude
  • LangChain
  • Pinecone
  • pgvector
  • Vercel AI SDK

Fix RAG pipeline issues — your questions, answered

How much does it cost to fix RAG Pipeline Issues?

Pricing starts from $3,500 and depends on the scope we find during the diagnostic. You get a fixed, written quote before any work begins — most engagements like this run 2–6 weeks.

How long does it take to fix RAG Pipeline Issues?

Typically 2–6 weeks for a focused engagement. After a short diagnostic we commit to a firm timeline so you know exactly what to expect.

Will you work directly on our existing codebase?

Yes. We work on your GitHub, GitLab or Bitbucket, ship every change as a pull request you review, and follow your code-review standards — not ours.

What exactly will I have at the end?

Concrete, documented outcomes — Evaluation harness with scored test cases, Implementation behind feature flags + rollback plan, Cost & latency dashboard wired to your observability, and more. No black-box agency report.

How quickly can you start, and do you sign an NDA?

For a focused task like this we can usually start within 24–48 hours of the brief. We sign an NDA on day one, before we look at any code — yours or ours.

How do you make sure a model or prompt change is actually better?

We build a scored evaluation harness — golden set plus LLM-as-judge and human spot-checks — and gate changes against it, so you ship improvements you can prove instead of regressions you can't see.

Let's get this off your plate

Send a 60-second brief on Fix RAG Pipeline Issues and a senior engineer replies within 24 hours with a plan and a fixed quote. NDA on day one, no retainer required.